From 0b34b1a0cfa798bf6b20473a3f8852684ddd000f Mon Sep 17 00:00:00 2001 From: gurdeep330 Date: Tue, 5 Mar 2024 16:48:19 +0100 Subject: [PATCH] update --- .github/workflows/mkdocs-deploy.yml | 15 +- app/code/literatureFetch.py | 65 +- app/code/utils.py | 62 +- app/data/query2.tsv | 2 + custom_theme/404.html | 1 - docs/All.md | 316 ++++++-- docs/Koopman_Theory.md | 316 ++++++-- docs/Latent_Space_Simulator.md | 316 ++++++-- docs/Neural_ODEs.md | 964 +++++++++++++++++++++++-- docs/PINNs.md | 322 +++++++-- docs/Physics-informed_GNNs.md | 964 +++++++++++++++++++++++-- docs/Symbolic_regression.md | 324 +++++++-- docs/assets/All.png | Bin 48566 -> 48741 bytes docs/assets/Koopman_Theory.png | Bin 46901 -> 46866 bytes docs/assets/Latent_Space_Simulator.png | Bin 54190 -> 54303 bytes docs/assets/Neural_ODEs.png | Bin 42866 -> 43222 bytes docs/assets/Physics-informed_GNNs.png | Bin 48853 -> 48816 bytes docs/assets/Symbolic_regression.png | Bin 48112 -> 48064 bytes mkdocs.yml | 25 +- overrides/main.html | 12 +- templates/category.txt | 89 ++- 21 files changed, 3258 insertions(+), 535 deletions(-) create mode 100644 app/data/query2.tsv delete mode 100644 custom_theme/404.html diff --git a/.github/workflows/mkdocs-deploy.yml b/.github/workflows/mkdocs-deploy.yml index 70bb5310..ebb39aa4 100644 --- a/.github/workflows/mkdocs-deploy.yml +++ b/.github/workflows/mkdocs-deploy.yml @@ -35,4 +35,17 @@ jobs: restore-keys: | mkdocs-material- - run: pip install mkdocs-material - - run: mkdocs gh-deploy --force \ No newline at end of file + - run: mkdocs gh-deploy --force + # commit + - name: Commit files + run: | + git config --local user.email "action@github.com" + git config --local user.name "GitHub Action" + git add -A + git commit -m "update data" -a + # push + - name: Push changes + uses: ad-m/github-push-action@v0.6.0 + with: + github_token: ${{ secrets.GITHUB_TOKEN }} + branch: main \ No newline at end of file diff --git a/app/code/literatureFetch.py b/app/code/literatureFetch.py index ae5aadaa..03205dc7 100755 --- a/app/code/literatureFetch.py +++ b/app/code/literatureFetch.py @@ -19,13 +19,11 @@ # 'limit': 5, 'publicationTypes': 'JournalArticle', # 'year': '2020-', - 'fields': 'paperId,url,journal,\ - title,publicationTypes,publicationDate,\ - citationCount,publicationVenue', + 'fields': 'paperId,url,journal,title,publicationTypes,publicationDate,citationCount,publicationVenue', # 'sort': 'citationCount:desc', 'token': None } -N = 10 +N = 50 DIC = {} def fetch_articles(search_query, @@ -48,7 +46,6 @@ def fetch_articles(search_query, while True: # Make the GET request to the paper search endpoint with the URL and query parameters search_response = requests.get(URL, params=query_params, timeout=None) - print ('status code', search_response.status_code) # WHen the status code is 429, sleep for 5 minutes # if search_response.status_code == 429: # status_code_429 += 1 @@ -58,8 +55,13 @@ def fetch_articles(search_query, # time.sleep(310) # continue # When the status code is 200, break the loop - if search_response.status_code == 200: + if search_response.status_code != 200: + print ('status code', search_response.status_code) + print ('Sleeping for 3 seconds....') + time.sleep(3) + else: break + search_response_json = search_response.json() fetched_data += search_response_json['data'] # End the loop if we have fetched enough data @@ -70,9 +72,25 @@ def fetch_articles(search_query, # if the token is not None if search_response_json['token'] is not None: query_params['token'] = search_response_json['token'] + + # fix the publicationVenue and journal + for paper in fetched_data: + # print (paper) + publication_venue = paper['publicationVenue'] + if publication_venue is None: + paper['publicationVenue'] = 'NA' + elif 'name' in publication_venue: + paper['publicationVenue'] = publication_venue['name'] + else: + paper['publicationVenue'] = '' + journal = paper['journal'] + if journal is None: + paper['journal'] = 'NA' + elif 'name' in journal: + paper['journal'] = journal['name'] return fetched_data -def create_template(template_file, category_name) -> str: +def create_template(template_file, category_name, df) -> str: """ Return the markdown content for a given template @@ -94,7 +112,9 @@ def create_template(template_file, category_name) -> str: category_name=category_name, title=DIC[category_name]['title'], query=DIC[category_name]['query'], - hide_nav="---\nhide:\n\t- navigation---\n", + x_year=df['Year'].tolist(), + y_num_articles=df['num_articles'].tolist(), + y_num_citations=df['num_citations'].tolist() ) # return markdownify.markdownify(content) return content @@ -109,6 +129,7 @@ def main(): Returns: None """ + # Work with all the categories in the file with open('../data/query.tsv', 'r', encoding='utf-8') as f: for line in f: @@ -122,14 +143,15 @@ def main(): ## Fetch the most cited articles data = fetch_articles(query) DIC[category_name] = {'title': title, 'query': query, 'most_cited_articles': data} - plot = utils.metrics_over_time(data, category_name, title) - plot.savefig(f'../../docs/assets/{category_name}.png') + # plot = utils.metrics_over_time_js(data, category_name, title) + # plot.savefig(f'../../docs/assets/{category_name}.png') + df = utils.metrics_over_time_js(data, category_name, title) ################################ ## Fetch the most recent articles data = fetch_articles(query, sort = 'publicationDate:desc') DIC[category_name]['most_recent_articles'] = data # print (data[0]) - markdown_text = create_template("category.txt", category_name) + markdown_text = create_template("category.txt", category_name, df) # DIC[category_name]['most_cited_articles'][0:N], # DIC[category_name]['most_recent_articles'][0:N]) # Add the hide navigation @@ -147,14 +169,15 @@ def main(): ## Fetch the most cited articles data = fetch_articles(query) DIC[category_name] = {'title': title, 'query': query, 'most_cited_articles': data} - plot = utils.metrics_over_time(data, category_name, title) - plot.savefig(f'../../docs/assets/{category_name}.png') + # plot = utils.metrics_over_time_js(data, category_name, title) + # plot.savefig(f'../../docs/assets/{category_name}.png') + df = utils.metrics_over_time_js(data, category_name, title) ################################ ## Fetch the most recent articles data = fetch_articles(query, sort = 'publicationDate:desc') DIC[category_name]['most_recent_articles'] = data # print (data[0]) - markdown_text = create_template("category.txt", category_name) + markdown_text = create_template("category.txt", category_name, df) # DIC[category_name]['most_cited_articles'][0:N], # DIC[category_name]['most_recent_articles'][0:N]) # Add the hide navigation @@ -163,6 +186,20 @@ def main(): with open(f'../../docs/{category_name}.md', 'w', encoding='utf-8') as file: file.write(markdown_text) ################################ + + # Read YAML file + file_path = '../../base.yml' + data = utils.read_yaml(file_path) + print (data['nav']) + + # Add more stuff to the YAML data + data['nav'] = [] + for category_name, category_items in DIC.items(): + data['nav'].append({category_items['title']: category_name + '.md'}) + + print (data['nav']) + # Write modified YAML data back to file + # write_yaml(data, file_path) if __name__ == '__main__': # Run the main function diff --git a/app/code/utils.py b/app/code/utils.py index 85c56805..0b03e44f 100755 --- a/app/code/utils.py +++ b/app/code/utils.py @@ -6,6 +6,7 @@ import matplotlib.pyplot as plt import pandas as pd +import yaml def metrics_over_time(data, category_name, title) -> plt: """ @@ -75,4 +76,63 @@ def metrics_over_time(data, category_name, title) -> plt: return plt - #A26, B1 \ No newline at end of file + #A26, B1 + +def metrics_over_time_js(data, category_name, title) -> plt: + """ + Return the metrics over time + + Args: + data (list): list of dictionaries + category_name (str): category name + title (str): title of the graph + + Returns: + None + + Example: + data = [ + { + 'title': 'title1', + 'publicationDate': '2020-01-01', + 'citationCount': 10 + }, + { + 'title': 'title2', + 'publicationDate': '2020-01-01', + 'citationCount': 10 + } + ] + """ + dic = {} + for paper in data: + publication_date = paper['publicationDate'] + if publication_date is None or publication_date == '': + continue + year = publication_date.split('-')[0] + if year not in dic: + dic[year] = {'num_articles': 0, 'num_citations': 0} + dic[year]['num_articles'] += 1 + citation_count = paper['citationCount'] + if citation_count is None or citation_count == '': + continue + dic[year]['num_citations'] += citation_count + # Using noc and yop, plot the line graph with years on x-axis and number of citations on y-axis + df = pd.DataFrame(dic).T + # Make another colum for the year + df['Year'] = df.index + # Sort by year + df = df.sort_values(by='Year', ascending=True) + # print (df) + return df + +# Function to read YAML file +def read_yaml(file_path): + with open(file_path, 'r') as file: + data = yaml.safe_load(file) + return data + +# Function to write YAML file +def write_yaml(data, file_path): + with open(file_path, 'w') as file: + yaml.dump(data, file, default_flow_style=False) diff --git a/app/data/query2.tsv b/app/data/query2.tsv new file mode 100644 index 00000000..f6a020b8 --- /dev/null +++ b/app/data/query2.tsv @@ -0,0 +1,2 @@ +Title Query +Neural ODEs Neural ODEs diff --git a/custom_theme/404.html b/custom_theme/404.html deleted file mode 100644 index 3b2634d5..00000000 --- a/custom_theme/404.html +++ /dev/null @@ -1 +0,0 @@ -

Hello

\ No newline at end of file diff --git a/docs/All.md b/docs/All.md index 361c1f66..614bf494 100644 --- a/docs/All.md +++ b/docs/All.md @@ -2,72 +2,250 @@ hide: - navigation --- - - - - - - - -### 1. Search query - - -*(neural ordinary differential equation) | (neural ODE) | (graph neural differential equation) | (graph neural diffusion) | (graph neural ODEs) | (graph networks) | (physics constrain) | (learned simulator) | (learned simulation) | ((symbolic regression) + dynamics) | (physics-informed neural computing) | (VAMP) | (latent space simul\*) | (decomposition of koopman operator) | (time-lagged autoencoder) | (koopman\*) | (transformations in hilbert space) | (linear transformation of PDEs) | (regularization of physics-informed machine learning)* - - - - -### 2. All articles and citations over time - - -![All](assets/All.png) - - - - -### 3. Most cited articles on All - - - - -| Title | PublicationDate | #Citations | Journal/Conference | publicationVenue | -| --- | --- | --- | --- | --- | -| [Gradient-based learning applied to document recognition](https://www.semanticscholar.org/paper/162d958ff885f1462aeda91cd72582323fd6a1f4) | None | 46003 | {'name': 'Proc. IEEE', 'pages': '2278-2324', 'volume': '86'} | {'id': '6faaccca-1cc4-45a9-aeb6-96a4901d2606', 'name': 'Proceedings of the IEEE', 'type': 'journal', 'alternate\_names': ['Proc IEEE'], 'issn': '0018-9219', 'alternate\_issns': ['1558-2256'], 'url': 'http://www.ieee.org/portal/pages/pubs/proceedings/', 'alternate\_urls': ['http://www.ieee.org/products/onlinepubs/pub/about\_conference.html', 'https://ieeexplore.ieee.org/servlet/opac?punumber=5', 'http://proceedingsoftheieee.ieee.org/']} | -| [Collective dynamics of ‘small-world’ networks](https://www.semanticscholar.org/paper/d61031326150ba23f90e6587c13d99188209250e) | 1998-06-04 | 38484 | {'name': 'Nature', 'pages': '440-442', 'volume': '393'} | {'id': '6c24a0a0-b07d-4d7b-a19b-fd09a3ed453a', 'name': 'Nature', 'type': 'journal', 'issn': '0028-0836', 'url': 'https://www.nature.com/', 'alternate\_urls': ['http://www.nature.com/nature/', 'https://www.nature.com/nature/', 'http://www.nature.com/nature/archive/index.html']} | -| [Semi-Supervised Classification with Graph Convolutional Networks](https://www.semanticscholar.org/paper/36eff562f65125511b5dfab68ce7f7a943c27478) | 2016-09-09 | 22114 | {'name': 'ArXiv', 'volume': 'abs/1609.02907'} | {'id': '939c6e1d-0d17-4d6e-8a82-66d960df0e40', 'name': 'International Conference on Learning Representations', 'type': 'conference', 'alternate\_names': ['Int Conf Learn Represent', 'ICLR'], 'url': 'https://iclr.cc/'} | -| [Statistical mechanics of complex networks](https://www.semanticscholar.org/paper/dce8146987557735a19771aefa1f027211a2c275) | 2001-06-06 | 18824 | {'name': 'ArXiv', 'volume': 'cond-mat/0106096'} | {'id': '1901e811-ee72-4b20-8f7e-de08cd395a10', 'name': 'arXiv.org', 'alternate\_names': ['ArXiv'], 'issn': '2331-8422', 'url': 'https://arxiv.org'} | -| [The Structure and Function of Complex Networks](https://www.semanticscholar.org/paper/e6c4925fb114d13a8568f88957c167c928f0c9f1) | 2003-03-25 | 16785 | {'name': 'SIAM Rev.', 'pages': '167-256', 'volume': '45'} | {'id': '8f59dd66-e4cd-4341-8ea9-9a03d965a009', 'name': 'SIAM Review', 'type': 'journal', 'alternate\_names': ['SIAM Rev', 'Siam Rev', 'Siam Review'], 'issn': '0036-1445', 'url': 'https://www.jstor.org/journal/siamreview', 'alternate\_urls': ['http://www.jstor.org/journals/00361445.html', 'https://epubs.siam.org/journal/siread', 'http://www.siam.org/journals/sirev.php']} | -| [TensorFlow: A system for large-scale machine learning](https://www.semanticscholar.org/paper/4954fa180728932959997a4768411ff9136aac81) | 2016-05-27 | 16703 | {'pages': '265-283'} | {'id': '86c43745-31d9-4c1a-b33f-ce3aa0042dbb', 'name': 'USENIX Symposium on Operating Systems Design and Implementation', 'type': 'conference', 'alternate\_names': ['Oper Syst Des Implement', 'Operating Systems Design and Implementation', 'OSDI', 'USENIX Symp Oper Syst Des Implement']} | -| [Community structure in social and biological networks](https://www.semanticscholar.org/paper/2a005868b79511cf8c924cd5990e2497527a0527) | 2001-12-07 | 14280 | {'name': 'Proceedings of the National Academy of Sciences of the United States of America', 'pages': '7821 - 7826', 'volume': '99'} | {'id': 'bb95bf2e-8383-4748-bf9d-d6906d091085', 'name': 'Proceedings of the National Academy of Sciences of the United States of America', 'type': 'journal', 'alternate\_names': ['PNAS', 'PNAS online', 'Proceedings of the National Academy of Sciences of the United States of America.', 'Proc National Acad Sci', 'Proceedings of the National Academy of Sciences', 'Proc National Acad Sci u s Am'], 'issn': '0027-8424', 'alternate\_issns': ['1091-6490'], 'url': 'https://www.jstor.org/journal/procnatiacadscie', 'alternate\_urls': ['http://www.pnas.org/', 'https://www.pnas.org/', 'http://www.jstor.org/journals/00278424.html', 'www.pnas.org/']} | -| [Graph Attention Networks](https://www.semanticscholar.org/paper/33998aff64ce51df8dee45989cdca4b6b1329ec4) | 2017-10-30 | 13972 | {'name': 'ArXiv', 'volume': 'abs/1710.10903'} | {'id': '939c6e1d-0d17-4d6e-8a82-66d960df0e40', 'name': 'International Conference on Learning Representations', 'type': 'conference', 'alternate\_names': ['Int Conf Learn Represent', 'ICLR'], 'url': 'https://iclr.cc/'} | -| [PRISMA Extension for Scoping Reviews (PRISMA-ScR): Checklist and Explanation](https://www.semanticscholar.org/paper/450106c6c960424b365249f2a301ce0abe24e346) | 2018-10-02 | 12792 | {'name': 'Annals of Internal Medicine', 'pages': '467-473', 'volume': '169'} | {'id': '643b0c17-99ac-463b-81c4-df44ad66e34d', 'name': 'Annals of Internal Medicine', 'type': 'journal', 'alternate\_names': ['Ann Intern Med'], 'issn': '0003-4819', 'url': 'http://www.acponline.org/journals/annals/annaltoc.htm', 'alternate\_urls': ['http://www.annals.org/']} | -| [Consensus problems in networks of agents with switching topology and time-delays](https://www.semanticscholar.org/paper/9839ed2281ba4b589bf88c7e4acc48c9fa6fb933) | 2004-09-13 | 11249 | {'name': 'IEEE Transactions on Automatic Control', 'pages': '1520-1533', 'volume': '49'} | {'id': '1283a59c-0d1f-48c3-81d7-02172f597e70', 'name': 'IEEE Transactions on Automatic Control', 'type': 'journal', 'alternate\_names': ['IEEE Trans Autom Control'], 'issn': '0018-9286', 'url': 'http://ieeexplore.ieee.org/servlet/opac?punumber=9'} | - - - - - - -### 4. Latest articles on All - - - - -| Title | PublicationDate | #Citations | Journal/Conference | publicationVenue | -| --- | --- | --- | --- | --- | -| [Hierarchical spatio-temporal graph convolutional neural networks for traffic data imputation](https://www.semanticscholar.org/paper/04744b6893487a608e3726fb4542e2a7f9e81a5b) | 2024-06-01 | 0 | {'name': 'Information Fusion'} | {'id': '06afdd0b-0d85-413f-af8a-c3045c12c561', 'name': 'Information Fusion', 'type': 'journal', 'alternate\_names': ['Inf Fusion'], 'issn': '1566-2535', 'url': 'https://www.journals.elsevier.com/information-fusion', 'alternate\_urls': ['http://www.sciencedirect.com/science/journal/15662535']} | -| [Reagent dosage inference based on graph convolutional memory perception network for zinc roughing flotation](https://www.semanticscholar.org/paper/ba23319a62da63ec3b664f6452bb7a9aee8a46dc) | 2024-05-01 | 0 | {'name': 'Control Engineering Practice'} | {'id': 'af74e393-8f45-41cd-915b-734494cb48f2', 'name': 'Control Engineering Practice', 'type': 'journal', 'alternate\_names': ['Control Eng Pract'], 'issn': '0967-0661', 'url': 'http://www.elsevier.com/wps/find/journaldescription.cws\_home/123/description#description', 'alternate\_urls': ['http://www.sciencedirect.com/science/journal/09670661']} | -| [MACNS: A generic graph neural network integrated deep reinforcement learning based multi-agent collaborative navigation system for dynamic trajectory planning](https://www.semanticscholar.org/paper/a1a503c7c23502bebe94eb042b0ce9f8bdbb6504) | 2024-05-01 | 0 | {'name': 'Inf. Fusion', 'pages': '102250', 'volume': '105'} | {'id': '06afdd0b-0d85-413f-af8a-c3045c12c561', 'name': 'Information Fusion', 'type': 'journal', 'alternate\_names': ['Inf Fusion'], 'issn': '1566-2535', 'url': 'https://www.journals.elsevier.com/information-fusion', 'alternate\_urls': ['http://www.sciencedirect.com/science/journal/15662535']} | -| [DawnGNN: Documentation augmented windows malware detection using graph neural network](https://www.semanticscholar.org/paper/45cb2614652147789e18f1bc15d665977d2d1ee9) | 2024-05-01 | 0 | {'name': 'Computers & Security'} | None | -| [Multi-level Graph Memory Network Cluster Convolutional Recurrent Network for traffic forecasting](https://www.semanticscholar.org/paper/357677ec8b2223f049c45c7330633a5b85c2bc95) | 2024-05-01 | 0 | {'name': 'Inf. Fusion', 'pages': '102214', 'volume': '105'} | {'id': '06afdd0b-0d85-413f-af8a-c3045c12c561', 'name': 'Information Fusion', 'type': 'journal', 'alternate\_names': ['Inf Fusion'], 'issn': '1566-2535', 'url': 'https://www.journals.elsevier.com/information-fusion', 'alternate\_urls': ['http://www.sciencedirect.com/science/journal/15662535']} | -| [FairCare: Adversarial training of a heterogeneous graph neural network with attention mechanism to learn fair representations of electronic health records](https://www.semanticscholar.org/paper/3383c82d39b88e5349d345e32e879806bd72d435) | 2024-05-01 | 0 | {'name': 'Information Processing & Management'} | None | -| [Multi-criteria group decision making based on graph neural networks in Pythagorean fuzzy environment](https://www.semanticscholar.org/paper/13a50769f110029fcb3390956789aec236071c53) | 2024-05-01 | 1 | {'name': 'Expert Systems with Applications'} | {'id': '987139ae-a65d-49bb-aaf6-fb764dc40b19', 'name': 'Expert systems with applications', 'type': 'journal', 'alternate\_names': ['Expert syst appl', 'Expert Systems With Applications', 'Expert Syst Appl'], 'issn': '0957-4174', 'url': 'https://www.journals.elsevier.com/expert-systems-with-applications/', 'alternate\_urls': ['https://www.sciencedirect.com/journal/expert-systems-with-applications', 'http://www.sciencedirect.com/science/journal/09574174']} | -| [POI recommendation for random groups based on cooperative graph neural networks](https://www.semanticscholar.org/paper/0cfd9a1774cf41ff07e957bbc25d14596d529c4f) | 2024-05-01 | 0 | {'name': 'Information Processing & Management'} | None | -| [Attention based multi-task interpretable graph convolutional network for Alzheimer’s disease analysis](https://www.semanticscholar.org/paper/fc5ee86473fd698e3f4405b51bdfe0575304a30d) | 2024-04-01 | 0 | {'name': 'Pattern Recognition Letters'} | {'id': 'f35e3e87-9df4-497b-aa0d-bb8584197290', 'name': 'Pattern Recognition Letters', 'type': 'journal', 'alternate\_names': ['Pattern Recognit Lett'], 'issn': '0167-8655', 'url': 'https://www.journals.elsevier.com/pattern-recognition-letters/', 'alternate\_urls': ['http://www.journals.elsevier.com/pattern-recognition-letters/', 'http://www.sciencedirect.com/science/journal/01678655']} | -| [A coarse-to-fine adaptive spatial–temporal graph convolution network with residuals for motor imagery decoding from the same limb](https://www.semanticscholar.org/paper/f56be81f12e0c0bdf632d5feeaf028dfb791223a) | 2024-04-01 | 0 | {'name': 'Biomedical Signal Processing and Control'} | {'id': '1bac31b4-014a-4981-ae41-af2a40acc162', 'name': 'Biomedical Signal Processing and Control', 'type': 'journal', 'alternate\_names': ['Biomed Signal Process Control'], 'issn': '1746-8094', 'url': 'https://www.journals.elsevier.com/biomedical-signal-processing-and-control', 'alternate\_urls': ['http://www.sciencedirect.com/science/journal/17468094']} | - - - - - - + + + + + + + + +

+

1. Search query

+ (neural ordinary differential equation) | (neural ODE) | (graph neural differential equation) | (graph neural diffusion) | (graph neural ODEs) | (graph networks) | (physics constrain) | (learned simulator) | (learned simulation) | ((symbolic regression) + dynamics) | (physics-informed neural computing) | (VAMP) | (latent space simul*) | (decomposition of koopman operator) | (time-lagged autoencoder) | (koopman*) | (transformations in hilbert space) | (linear transformation of PDEs) | (regularization of physics-informed machine learning) +

+ +

+

2. All articles and citations over time

+
+ +
+

+ +

+

3. Most cited articles on All

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
TitlePublicationDate#CitationsJournal/ConferencepublicationVenue
Gradient-based learning applied to document recognitionNone46007Proc. IEEEProceedings of the IEEE
Collective dynamics of ‘small-world’ networks1998-06-0438487NatureNature
Semi-Supervised Classification with Graph Convolutional Networks2016-09-0922124ArXivInternational Conference on Learning Representations
Statistical mechanics of complex networks2001-06-0618824ArXivarXiv.org
The Structure and Function of Complex Networks2003-03-2516784SIAM Rev.SIAM Review
TensorFlow: A system for large-scale machine learning2016-05-2716709{'pages': '265-283'}USENIX Symposium on Operating Systems Design and Implementation
Community structure in social and biological networks2001-12-0714280Proceedings of the National Academy of Sciences of the United States of AmericaProceedings of the National Academy of Sciences of the United States of America
Graph Attention Networks2017-10-3013990ArXivInternational Conference on Learning Representations
PRISMA Extension for Scoping Reviews (PRISMA-ScR): Checklist and Explanation2018-10-0212793Annals of Internal MedicineAnnals of Internal Medicine
Consensus problems in networks of agents with switching topology and time-delays2004-09-1311249IEEE Transactions on Automatic ControlIEEE Transactions on Automatic Control
+

+ +

+

4. Latest articles on All

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
TitlePublicationDate#CitationsJournal/ConferencepublicationVenue
Hierarchical spatio-temporal graph convolutional neural networks for traffic data imputation2024-06-010Information FusionInformation Fusion
Reagent dosage inference based on graph convolutional memory perception network for zinc roughing flotation2024-05-010Control Engineering PracticeControl Engineering Practice
MACNS: A generic graph neural network integrated deep reinforcement learning based multi-agent collaborative navigation system for dynamic trajectory planning2024-05-010Inf. FusionInformation Fusion
DawnGNN: Documentation augmented windows malware detection using graph neural network2024-05-010Computers & SecurityNA
Multi-level Graph Memory Network Cluster Convolutional Recurrent Network for traffic forecasting2024-05-010Inf. FusionInformation Fusion
FairCare: Adversarial training of a heterogeneous graph neural network with attention mechanism to learn fair representations of electronic health records2024-05-010Information Processing & ManagementNA
Multi-criteria group decision making based on graph neural networks in Pythagorean fuzzy environment2024-05-011Expert Systems with ApplicationsExpert systems with applications
POI recommendation for random groups based on cooperative graph neural networks2024-05-010Information Processing & ManagementNA
Attention based multi-task interpretable graph convolutional network for Alzheimer’s disease analysis2024-04-010Pattern Recognition LettersPattern Recognition Letters
A coarse-to-fine adaptive spatial–temporal graph convolution network with residuals for motor imagery decoding from the same limb2024-04-010Biomedical Signal Processing and ControlBiomedical Signal Processing and Control
+

+ + + + + \ No newline at end of file diff --git a/docs/Koopman_Theory.md b/docs/Koopman_Theory.md index e1d4199d..66f33b50 100644 --- a/docs/Koopman_Theory.md +++ b/docs/Koopman_Theory.md @@ -2,72 +2,250 @@ hide: - navigation --- - - - - - - - -### 1. Search query - - -*(koopman\*) | (transformations in hilbert space) | (linear transformation of PDEs) | (regularization of physics-informed machine learning)* - - - - -### 2. Koopman Theory articles and citations over time - - -![Koopman Theory](assets/Koopman_Theory.png) - - - - -### 3. Most cited articles on Koopman Theory - - - - -| Title | PublicationDate | #Citations | Journal/Conference | publicationVenue | -| --- | --- | --- | --- | --- | -| [Hamiltonian Systems and Transformation in Hilbert Space.](https://www.semanticscholar.org/paper/bf657b5049c1a5c839369d3948ffb4c0584cd1d2) | 1931-05-01 | 1558 | {'name': 'Proceedings of the National Academy of Sciences of the United States of America', 'pages': '\n 315-8\n ', 'volume': '17 5'} | {'id': 'bb95bf2e-8383-4748-bf9d-d6906d091085', 'name': 'Proceedings of the National Academy of Sciences of the United States of America', 'type': 'journal', 'alternate\_names': ['PNAS', 'PNAS online', 'Proceedings of the National Academy of Sciences of the United States of America.', 'Proc National Acad Sci', 'Proceedings of the National Academy of Sciences', 'Proc National Acad Sci u s Am'], 'issn': '0027-8424', 'alternate\_issns': ['1091-6490'], 'url': 'https://www.jstor.org/journal/procnatiacadscie', 'alternate\_urls': ['http://www.pnas.org/', 'https://www.pnas.org/', 'http://www.jstor.org/journals/00278424.html', 'www.pnas.org/']} | -| [A Data–Driven Approximation of the Koopman Operator: Extending Dynamic Mode Decomposition](https://www.semanticscholar.org/paper/10cab2f43c29fe12e5a0d0718eb6e1ff8c9d4777) | 2014-08-19 | 1323 | {'name': 'Journal of Nonlinear Science', 'pages': '1307 - 1346', 'volume': '25'} | {'id': '619f4cc3-1d00-4060-b88d-9854843ac2c2', 'name': 'Journal of nonlinear science', 'type': 'journal', 'alternate\_names': ['J Nonlinear Sci', 'Journal of Nonlinear Science', 'J nonlinear sci'], 'issn': '0938-8974', 'url': 'https://link.springer.com/journal/332'} | -| [Deep learning for universal linear embeddings of nonlinear dynamics](https://www.semanticscholar.org/paper/6adeda1af8abc6bc3c17c0b39f635a845476cd9f) | 2017-12-27 | 899 | {'name': 'Nature Communications', 'volume': '9'} | {'id': '43b3f0f9-489a-4566-8164-02fafde3cd98', 'name': 'Nature Communications', 'type': 'journal', 'alternate\_names': ['Nat Commun'], 'issn': '2041-1723', 'url': 'https://www.nature.com/ncomms/', 'alternate\_urls': ['http://www.nature.com/ncomms/about/index.html', 'http://www.nature.com/ncomms/index.html']} | -| [Entanglement renormalization.](https://www.semanticscholar.org/paper/7e54d86fb36907b99ef0580bfaea9b43c5942ae7) | 2005-12-08 | 784 | {'name': 'Physical review letters', 'pages': '\n 220405\n ', 'volume': '99 22'} | {'id': '16c9f9d4-bee1-435d-8c85-22a3deba109d', 'name': 'Physical Review Letters', 'type': 'journal', 'alternate\_names': ['Phys Rev Lett'], 'issn': '0031-9007', 'url': 'https://journals.aps.org/prl/', 'alternate\_urls': ['http://journals.aps.org/prl/', 'http://prl.aps.org/']} | -| [Applied Koopmanism.](https://www.semanticscholar.org/paper/2c9be1e38f978f43427ea5293b3138e0c4fede71) | 2012-06-14 | 694 | {'name': 'Chaos', 'pages': '\n 047510\n ', 'volume': '22 4'} | {'id': '30c0ded7-c8b4-473c-bbc0-f237234ac1a6', 'name': 'Chaos', 'type': 'journal', 'issn': '1054-1500', 'url': 'http://chaos.aip.org/', 'alternate\_urls': ['https://aip.scitation.org/journal/cha']} | -| [CT Imaging of the 2019 Novel Coronavirus (2019-nCoV) Pneumonia](https://www.semanticscholar.org/paper/b90161898ff5ef4236f1c19a5c88138e1c80c5ea) | 2020-01-31 | 658 | {'name': 'Radiology'} | {'id': '357207a3-a4af-4091-822c-75ef52d02fb5', 'name': 'Radiology', 'type': 'journal', 'issn': '0033-8419', 'url': 'http://radiology.rsna.org/', 'alternate\_urls': ['http://radiology.rsnajnls.org/']} | -| [Variants of Dynamic Mode Decomposition: Boundary Condition, Koopman, and Fourier Analyses](https://www.semanticscholar.org/paper/82e19123c7fdf1c047531eec5bce6f925dcc5ad5) | 2012-04-27 | 642 | {'name': 'Journal of Nonlinear Science', 'pages': '887-915', 'volume': '22'} | {'id': '619f4cc3-1d00-4060-b88d-9854843ac2c2', 'name': 'Journal of nonlinear science', 'type': 'journal', 'alternate\_names': ['J Nonlinear Sci', 'Journal of Nonlinear Science', 'J nonlinear sci'], 'issn': '0938-8974', 'url': 'https://link.springer.com/journal/332'} | -| [Linear predictors for nonlinear dynamical systems: Koopman operator meets model predictive control](https://www.semanticscholar.org/paper/dbb73c3f14600e3a746c643c2e8bece117de6be4) | 2016-11-10 | 635 | {'name': 'Autom.', 'pages': '149-160', 'volume': '93'} | None | -| [Algorithms for the Split Variational Inequality Problem](https://www.semanticscholar.org/paper/ff73ad9e51f79cc364545e7933f22cc2a74f28fc) | 2010-09-20 | 594 | {'name': 'Numerical Algorithms', 'pages': '301 - 323', 'volume': '59'} | {'id': '3920fb0a-e610-4b5d-8760-f43cfa321466', 'name': 'Numerical Algorithms', 'type': 'journal', 'alternate\_names': ['Numer Algorithm'], 'issn': '1017-1398', 'url': 'https://www.springer.com/computer/theoretical+computer+science/journal/11075?changeHeader', 'alternate\_urls': ['https://link.springer.com/journal/11075']} | -| [Quantum singular value transformation and beyond: exponential improvements for quantum matrix arithmetics](https://www.semanticscholar.org/paper/fa00b2c3d2fe8326470c47a3e5f5d1e716e58cb3) | 2018-06-05 | 472 | {'name': 'Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing'} | {'id': '8113a511-e0d9-4231-a1bc-0bf5d0212a4e', 'name': 'Symposium on the Theory of Computing', 'type': 'conference', 'alternate\_names': ['Symp Theory Comput', 'STOC'], 'url': 'http://acm-stoc.org/'} | - - - - - - -### 4. Latest articles on Koopman Theory - - - - -| Title | PublicationDate | #Citations | Journal/Conference | publicationVenue | -| --- | --- | --- | --- | --- | -| [A Data-Driven Koopman Approach for Power System Nonlinear Dynamic Observability Analysis](https://www.semanticscholar.org/paper/cf4e03fdbc78190194b74a5e1ad20465c5dd6463) | 2024-03-01 | 0 | {'name': 'IEEE Transactions on Power Systems', 'pages': '4090-4104', 'volume': '39'} | {'id': 'dbbda9ef-0504-4875-b893-5c964f6b8f0e', 'name': 'IEEE Transactions on Power Systems', 'type': 'journal', 'alternate\_names': ['IEEE Trans Power Syst'], 'issn': '0885-8950', 'url': 'http://ieeexplore.ieee.org/servlet/opac?punumber=59'} | -| [A Monte Carlo Approach to Koopman Direct Encoding and Its Application to the Learning of Neural-Network Observables](https://www.semanticscholar.org/paper/cabacb5b65447bbb8ef5f0f82c37cd1a66cf2282) | 2024-03-01 | 0 | {'name': 'IEEE Robotics and Automation Letters', 'pages': '2264-2271', 'volume': '9'} | {'id': '93c335b7-edf4-45f5-8ddc-7c5835154945', 'name': 'IEEE Robotics and Automation Letters', 'alternate\_names': ['IEEE Robot Autom Lett'], 'issn': '2377-3766', 'url': 'https://www.ieee.org/membership-catalog/productdetail/showProductDetailPage.html?product=PER481-ELE', 'alternate\_urls': ['http://ieeexplore.ieee.org/servlet/opac?punumber=7083369']} | -| [Improving potential energy surfaces using measured Feshbach resonance states](https://www.semanticscholar.org/paper/b5f96d19a20f448255c0e361b01caf9aeff87938) | 2024-03-01 | 0 | {'name': 'Science Advances', 'volume': '10'} | {'id': 'cb30f0c9-2980-4b7d-bbcb-68fc5472b97c', 'name': 'Science Advances', 'type': 'journal', 'alternate\_names': ['Sci Adv'], 'issn': '2375-2548', 'url': 'http://www.scienceadvances.org/', 'alternate\_urls': ['https://advances.sciencemag.org/']} | -| [Robust Three-Stage Dynamic Mode Decomposition for Analysis of Power System Oscillations](https://www.semanticscholar.org/paper/1a279d90354755f741f45618a5673e220a715fc7) | 2024-03-01 | 0 | {'name': 'IEEE Transactions on Power Systems', 'pages': '4000-4009', 'volume': '39'} | {'id': 'dbbda9ef-0504-4875-b893-5c964f6b8f0e', 'name': 'IEEE Transactions on Power Systems', 'type': 'journal', 'alternate\_names': ['IEEE Trans Power Syst'], 'issn': '0885-8950', 'url': 'http://ieeexplore.ieee.org/servlet/opac?punumber=59'} | -| [Data-Driven Transient Stability Evaluation of Electric Distribution Networks Dominated by EV Supercharging Stations](https://www.semanticscholar.org/paper/15757b898cf9ba88030c73486a039b5b296a118b) | 2024-03-01 | 0 | {'name': 'IEEE Transactions on Smart Grid', 'pages': '1939-1950', 'volume': '15'} | {'id': '1c2f3998-b5ca-48ca-9991-94b71c71ecb7', 'name': 'IEEE Transactions on Smart Grid', 'type': 'journal', 'alternate\_names': ['IEEE Trans Smart Grid'], 'issn': '1949-3053', 'url': 'http://ieeexplore.ieee.org/servlet/opac?punumber=5165411'} | -| [Approximation of discrete and orbital Koopman operators over subsets and manifolds](https://www.semanticscholar.org/paper/1d4ea3a7943c108bee09f107e42ffdf0fd3cfde3) | 2024-02-22 | 0 | {'name': 'Nonlinear Dynamics'} | {'id': '10925c1c-0929-4ec5-8268-a8a52bd84631', 'name': 'Nonlinear dynamics', 'type': 'journal', 'alternate\_names': ['Nonlinear Dyn', 'Nonlinear Dynamics', 'Nonlinear dyn'], 'issn': '0924-090X', 'url': 'http://www.springer.com/11071', 'alternate\_urls': ['https://link.springer.com/journal/11071']} | -| [Learning Hamiltonian neural Koopman operator and simultaneously sustaining and discovering conservation laws](https://www.semanticscholar.org/paper/8fc588323ba32123f635b9c7f7c1568a3f09ab38) | 2024-02-20 | 0 | {'name': 'Physical Review Research'} | {'id': '349f119f-f4ee-48cf-aedb-89bcb56ab8e3', 'name': 'Physical Review Research', 'type': 'journal', 'alternate\_names': ['Phys Rev Res'], 'issn': '2643-1564', 'url': 'https://journals.aps.org/prresearch'} | -| [Extraction of nonlinearity in neural networks and model compression with Koopman operator](https://www.semanticscholar.org/paper/f090e77e916fba1a8f28cd4c46a65b0f2c9ae494) | 2024-02-18 | 0 | {'name': 'ArXiv', 'volume': 'abs/2402.11740'} | {'id': '1901e811-ee72-4b20-8f7e-de08cd395a10', 'name': 'arXiv.org', 'alternate\_names': ['ArXiv'], 'issn': '2331-8422', 'url': 'https://arxiv.org'} | -| [Machine Learning based Prediction of Ditching Loads](https://www.semanticscholar.org/paper/cb1cf69a67974f03796db6657e21635ea6832285) | 2024-02-16 | 0 | {'name': 'ArXiv', 'volume': 'abs/2402.10724'} | {'id': '1901e811-ee72-4b20-8f7e-de08cd395a10', 'name': 'arXiv.org', 'alternate\_names': ['ArXiv'], 'issn': '2331-8422', 'url': 'https://arxiv.org'} | -| [Kolmogorov n-Widths for Multitask Physics-Informed Machine Learning (PIML) Methods: Towards Robust Metrics](https://www.semanticscholar.org/paper/4e9fbef5c8daddbad96e50c3e1da8614d7772a75) | 2024-02-16 | 0 | {'name': 'ArXiv', 'volume': 'abs/2402.11126'} | {'id': '1901e811-ee72-4b20-8f7e-de08cd395a10', 'name': 'arXiv.org', 'alternate\_names': ['ArXiv'], 'issn': '2331-8422', 'url': 'https://arxiv.org'} | - - - - - - + + + + + + + + +

+

1. Search query

+ (koopman*) | (transformations in hilbert space) | (linear transformation of PDEs) | (regularization of physics-informed machine learning) +

+ +

+

2. Koopman Theory articles and citations over time

+
+ +
+

+ +

+

3. Most cited articles on Koopman Theory

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
TitlePublicationDate#CitationsJournal/ConferencepublicationVenue
Hamiltonian Systems and Transformation in Hilbert Space.1931-05-011558Proceedings of the National Academy of Sciences of the United States of AmericaProceedings of the National Academy of Sciences of the United States of America
A Data–Driven Approximation of the Koopman Operator: Extending Dynamic Mode Decomposition2014-08-191323Journal of Nonlinear ScienceJournal of nonlinear science
Deep learning for universal linear embeddings of nonlinear dynamics2017-12-27900Nature CommunicationsNature Communications
Entanglement renormalization.2005-12-08784Physical review lettersPhysical Review Letters
Applied Koopmanism.2012-06-14694ChaosChaos
CT Imaging of the 2019 Novel Coronavirus (2019-nCoV) Pneumonia2020-01-31658RadiologyRadiology
Variants of Dynamic Mode Decomposition: Boundary Condition, Koopman, and Fourier Analyses2012-04-27642Journal of Nonlinear ScienceJournal of nonlinear science
Linear predictors for nonlinear dynamical systems: Koopman operator meets model predictive control2016-11-10635Autom.NA
Algorithms for the Split Variational Inequality Problem2010-09-20594Numerical AlgorithmsNumerical Algorithms
Quantum singular value transformation and beyond: exponential improvements for quantum matrix arithmetics2018-06-05472Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of ComputingSymposium on the Theory of Computing
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+ +

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4. Latest articles on Koopman Theory

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
TitlePublicationDate#CitationsJournal/ConferencepublicationVenue
A Data-Driven Koopman Approach for Power System Nonlinear Dynamic Observability Analysis2024-03-010IEEE Transactions on Power SystemsIEEE Transactions on Power Systems
A Monte Carlo Approach to Koopman Direct Encoding and Its Application to the Learning of Neural-Network Observables2024-03-010IEEE Robotics and Automation LettersIEEE Robotics and Automation Letters
Improving potential energy surfaces using measured Feshbach resonance states2024-03-010Science AdvancesScience Advances
Robust Three-Stage Dynamic Mode Decomposition for Analysis of Power System Oscillations2024-03-010IEEE Transactions on Power SystemsIEEE Transactions on Power Systems
Data-Driven Transient Stability Evaluation of Electric Distribution Networks Dominated by EV Supercharging Stations2024-03-010IEEE Transactions on Smart GridIEEE Transactions on Smart Grid
Approximation of discrete and orbital Koopman operators over subsets and manifolds2024-02-220Nonlinear DynamicsNonlinear dynamics
Learning Hamiltonian neural Koopman operator and simultaneously sustaining and discovering conservation laws2024-02-200Physical Review ResearchPhysical Review Research
Extraction of nonlinearity in neural networks and model compression with Koopman operator2024-02-180ArXivarXiv.org
Machine Learning based Prediction of Ditching Loads2024-02-160ArXivarXiv.org
Kolmogorov n-Widths for Multitask Physics-Informed Machine Learning (PIML) Methods: Towards Robust Metrics2024-02-160ArXivarXiv.org
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+ + + + + \ No newline at end of file diff --git a/docs/Latent_Space_Simulator.md b/docs/Latent_Space_Simulator.md index 3aa55897..e81d4ece 100644 --- a/docs/Latent_Space_Simulator.md +++ b/docs/Latent_Space_Simulator.md @@ -2,72 +2,250 @@ hide: - navigation --- - - - - - - - -### 1. Search query - - -*(VAMP) | (latent space simul\*) | (decomposition of koopman operator) | (time-lagged autoencoder)* - - - - -### 2. Latent Space Simulator articles and citations over time - - -![Latent Space Simulator](assets/Latent_Space_Simulator.png) - - - - -### 3. Most cited articles on Latent Space Simulator - - - - -| Title | PublicationDate | #Citations | Journal/Conference | publicationVenue | -| --- | --- | --- | --- | --- | -| [Denoising Diffusion Implicit Models](https://www.semanticscholar.org/paper/014576b866078524286802b1d0e18628520aa886) | 2020-10-06 | 2512 | {'name': 'ArXiv', 'volume': 'abs/2010.02502'} | {'id': '939c6e1d-0d17-4d6e-8a82-66d960df0e40', 'name': 'International Conference on Learning Representations', 'type': 'conference', 'alternate\_names': ['Int Conf Learn Represent', 'ICLR'], 'url': 'https://iclr.cc/'} | -| [GTM: The Generative Topographic Mapping](https://www.semanticscholar.org/paper/2639515c248f220c73d44688c0097a99b01e1474) | None | 1496 | {'name': 'Neural Computation', 'pages': '215-234', 'volume': '10'} | {'id': '69b9bcdd-8229-4a00-a6e0-00f0e99a2bf3', 'name': 'Neural Computation', 'type': 'journal', 'alternate\_names': ['Neural Comput'], 'issn': '0899-7667', 'url': 'http://cognet.mit.edu/library/journals/journal?issn=08997667', 'alternate\_urls': ['http://ieeexplore.ieee.org/servlet/opac?punumber=6720226', 'http://www.mitpressjournals.org/loi/neco', 'https://www.mitpressjournals.org/loi/neco']} | -| [A Data–Driven Approximation of the Koopman Operator: Extending Dynamic Mode Decomposition](https://www.semanticscholar.org/paper/10cab2f43c29fe12e5a0d0718eb6e1ff8c9d4777) | 2014-08-19 | 1323 | {'name': 'Journal of Nonlinear Science', 'pages': '1307 - 1346', 'volume': '25'} | {'id': '619f4cc3-1d00-4060-b88d-9854843ac2c2', 'name': 'Journal of nonlinear science', 'type': 'journal', 'alternate\_names': ['J Nonlinear Sci', 'Journal of Nonlinear Science', 'J nonlinear sci'], 'issn': '0938-8974', 'url': 'https://link.springer.com/journal/332'} | -| [Deep Autoencoding Gaussian Mixture Model for Unsupervised Anomaly Detection](https://www.semanticscholar.org/paper/dbc7401e3e75c40d3c720e7db3c906d48bd742d7) | 2018-02-15 | 1236 | {'name': '', 'volume': ''} | {'id': '939c6e1d-0d17-4d6e-8a82-66d960df0e40', 'name': 'International Conference on Learning Representations', 'type': 'conference', 'alternate\_names': ['Int Conf Learn Represent', 'ICLR'], 'url': 'https://iclr.cc/'} | -| [Botulinum neurotoxin A selectively cleaves the synaptic protein SNAP-25](https://www.semanticscholar.org/paper/8af762911107a585f12decd890c4bc5df67dc3fb) | 1993-09-09 | 1165 | {'name': 'Nature', 'pages': '160-163', 'volume': '365'} | {'id': '6c24a0a0-b07d-4d7b-a19b-fd09a3ed453a', 'name': 'Nature', 'type': 'journal', 'issn': '0028-0836', 'url': 'https://www.nature.com/', 'alternate\_urls': ['http://www.nature.com/nature/', 'https://www.nature.com/nature/', 'http://www.nature.com/nature/archive/index.html']} | -| [Poincaré Embeddings for Learning Hierarchical Representations](https://www.semanticscholar.org/paper/1590bd1bca945fc6ff50b8cdf2da14ea2061c79a) | 2017-05-22 | 1031 | {'name': 'ArXiv', 'volume': 'abs/1705.08039'} | {'id': 'd9720b90-d60b-48bc-9df8-87a30b9a60dd', 'name': 'Neural Information Processing Systems', 'type': 'conference', 'alternate\_names': ['Neural Inf Process Syst', 'NeurIPS', 'NIPS'], 'url': 'http://neurips.cc/'} | -| [Validation of information recorded on general practitioner based computerised data resource in the United Kingdom.](https://www.semanticscholar.org/paper/66a626038ce5c68c0b28a1d6b74a3a135338a11e) | 1991-03-30 | 877 | {'name': 'British Medical Journal', 'pages': '766 - 768', 'volume': '302'} | {'id': '3048b449-a773-4256-9bb5-5e61fbb61e52', 'name': 'British medical journal', 'type': 'journal', 'alternate\_names': ['BMJ (Clinical Research Edition)', 'British Medical Journal', 'Br Med J', 'BMJ (british Med J', 'The BMJ (British Medical Journal)', 'eBMJ', 'Br med j', 'BMJ (clinical Res Ed', 'Br Med J (clinical Res Ed', 'British Medical Journal (Clinical Research Edition)', 'BMJ'], 'issn': '1759-2151', 'alternate\_issns': ['1756-1833', '0959-8138', '1790-5249', '1106-5028', '1468-5833', '0267-0623', '1222-5835', '1576-9445', '1106-4226'], 'url': 'https://www.bmj.com/', 'alternate\_urls': ['http://www.ibmj.net/', 'https://www.jstor.org/journal/bmjbritmedj', 'http://www.jstor.org/journals/09598138.html', 'http://www.bmj.ro/', 'http://www.bmj.com/bmj/', 'http://www.bmj.com/thebmj', 'http://www.jstor.org/action/showPublication?journalCode=bmjbritmedj', 'http://www.jstor.org/action/showPublication?journalCode=britmedjclires', 'https://www.bmj.com/archive']} | -| [Cross-domain sentiment classification via spectral feature alignment](https://www.semanticscholar.org/paper/ca781a2fc31a28f653b222ca8afdedc90a009266) | 2010-04-26 | 792 | {'pages': '751-760'} | {'id': 'e07422f9-c065-40c3-a37b-75e98dce79fe', 'name': 'The Web Conference', 'type': 'conference', 'alternate\_names': ['Web Conf', 'WWW'], 'url': 'http://www.iw3c2.org/'} | -| [Synaptic vesicle membrane fusion complex: action of clostridial neurotoxins on assembly.](https://www.semanticscholar.org/paper/d0baba24df9807ea8fa812f477fc8cd57adfe116) | 1994-11-01 | 783 | {'name': 'The EMBO Journal', 'volume': '13'} | {'id': 'b89f0ede-6fa8-4dd2-a8a7-f54695a00323', 'name': 'EMBO Journal', 'type': 'journal', 'alternate\_names': ['The EMBO Journal', 'EMBO J'], 'issn': '0261-4189', 'url': 'http://embojournal.npgjournals.com/', 'alternate\_urls': ['http://emboj.embopress.org/']} | -| [VBF: Vector-Based Forwarding Protocol for Underwater Sensor Networks](https://www.semanticscholar.org/paper/631755c88361cdf537bbe1eff8bdf18c52d6c962) | 2006-05-15 | 732 | {'pages': '1216-1221'} | None | - - - - - - -### 4. Latest articles on Latent Space Simulator - - - - -| Title | PublicationDate | #Citations | Journal/Conference | publicationVenue | -| --- | --- | --- | --- | --- | -| [Topic Modeling on Document Networks With Dirichlet Optimal Transport Barycenter](https://www.semanticscholar.org/paper/f8db237dfcbac885f750f86939ce006268519cca) | 2024-03-01 | 0 | {'name': 'IEEE Transactions on Knowledge and Data Engineering', 'pages': '1328-1340', 'volume': '36'} | {'id': 'c6840156-ee10-4d78-8832-7f8909811576', 'name': 'IEEE Transactions on Knowledge and Data Engineering', 'type': 'journal', 'alternate\_names': ['IEEE Trans Knowl Data Eng'], 'issn': '1041-4347', 'url': 'https://www.computer.org/web/tkde', 'alternate\_urls': ['http://ieeexplore.ieee.org/servlet/opac?punumber=69']} | -| [Multiclass and Multilabel Classifications by Consensus and Complementarity-Based Multiview Latent Space Projection](https://www.semanticscholar.org/paper/bee3c8b32859202472c917dab5a4757afb46a79f) | 2024-03-01 | 0 | {'name': 'IEEE Transactions on Systems, Man, and Cybernetics: Systems', 'pages': '1705-1718', 'volume': '54'} | None | -| [Learning-Based Edge-Device Collaborative DNN Inference in IoVT Networks](https://www.semanticscholar.org/paper/81cabd91414b487f021c110ba9c70311ad6636e9) | 2024-03-01 | 0 | {'name': 'IEEE Internet of Things Journal', 'pages': '7989-8004', 'volume': '11'} | {'id': '228761ec-c40a-479b-8309-9dcbe9851bcd', 'name': 'IEEE Internet of Things Journal', 'type': 'journal', 'alternate\_names': ['IEEE Internet Thing J'], 'issn': '2327-4662', 'url': 'https://www.ieee.org/membership-catalog/productdetail/showProductDetailPage.html?product=PER288-ELE', 'alternate\_urls': ['https://ieeexplore.ieee.org/servlet/opac?punumber=6488907', 'https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6488907', 'http://ieee-iotj.org/#']} | -| [NeuralFloors: Conditional Street-Level Scene Generation From BEV Semantic Maps via Neural Fields](https://www.semanticscholar.org/paper/28c0ff11f5a18b051f591807d531429636fa8037) | 2024-03-01 | 0 | {'name': 'IEEE Robotics and Automation Letters', 'pages': '2431-2438', 'volume': '9'} | {'id': '93c335b7-edf4-45f5-8ddc-7c5835154945', 'name': 'IEEE Robotics and Automation Letters', 'alternate\_names': ['IEEE Robot Autom Lett'], 'issn': '2377-3766', 'url': 'https://www.ieee.org/membership-catalog/productdetail/showProductDetailPage.html?product=PER481-ELE', 'alternate\_urls': ['http://ieeexplore.ieee.org/servlet/opac?punumber=7083369']} | -| [Robust Three-Stage Dynamic Mode Decomposition for Analysis of Power System Oscillations](https://www.semanticscholar.org/paper/1a279d90354755f741f45618a5673e220a715fc7) | 2024-03-01 | 0 | {'name': 'IEEE Transactions on Power Systems', 'pages': '4000-4009', 'volume': '39'} | {'id': 'dbbda9ef-0504-4875-b893-5c964f6b8f0e', 'name': 'IEEE Transactions on Power Systems', 'type': 'journal', 'alternate\_names': ['IEEE Trans Power Syst'], 'issn': '0885-8950', 'url': 'http://ieeexplore.ieee.org/servlet/opac?punumber=59'} | -| [Vibration-based structural damage localization through a discriminant analysis strategy with cepstral coefficients](https://www.semanticscholar.org/paper/ad7af3dfb3aa9bf417a98e84fb3bab61f46fc04f) | 2024-02-28 | 0 | {'name': 'Structural Health Monitoring'} | {'id': '928c5b4b-9a67-473f-996e-bf7e28c1e736', 'name': 'Structural Health Monitoring', 'type': 'journal', 'alternate\_names': ['Struct Health Monit', 'Struct Health Monit Int J', 'Structural Health Monitoring-an International Journal'], 'issn': '1475-9217', 'url': 'https://journals.sagepub.com/home/shm', 'alternate\_urls': ['http://shm.sagepub.com/']} | -| [Spectral Time-Varying Pattern Causality and Its Application.](https://www.semanticscholar.org/paper/8129bbd354a9694aa23224775d4b612e427aa529) | 2024-02-28 | 0 | {'name': 'IEEE journal of biomedical and health informatics', 'volume': 'PP'} | {'id': 'eac74c9c-a5c0-417d-8088-8164a6a8bfb3', 'name': 'IEEE journal of biomedical and health informatics', 'type': 'journal', 'alternate\_names': ['IEEE Journal of Biomedical and Health Informatics', 'IEEE j biomed health informatics', 'IEEE J Biomed Health Informatics'], 'issn': '2168-2194', 'url': 'https://ieeexplore.ieee.org/xpl/aboutJournal.jsp?punumber=6221020', 'alternate\_urls': ['https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6221020']} | -| [Big topic modeling based on a two-level hierarchical latent Beta-Liouville allocation for large-scale data and parameter streaming](https://www.semanticscholar.org/paper/714a07ff77f81ded2fd359c97468890d12a3dad2) | 2024-02-28 | 0 | {'name': 'Pattern Analysis and Applications', 'pages': '1-21', 'volume': '27'} | {'id': '69d98769-bd34-4c40-a508-895b6adfac86', 'name': 'Pattern Analysis and Applications', 'type': 'journal', 'alternate\_names': ['Pattern Anal Appl'], 'issn': '1433-7541', 'url': 'https://rd.springer.com/journal/10044'} | -| [Sensor based Dance Coherent Action Generation Model using Deep Learning Framework](https://www.semanticscholar.org/paper/78b968af546e846d26bd851a619c438a70c6ce68) | 2024-02-24 | 0 | {'name': 'Scalable Computing: Practice and Experience'} | None | -| [Monstrous Mushrooms, Toxic Love and Queer Utopias in Jenny Hval's Paradise Rot](https://www.semanticscholar.org/paper/cb8bbf850e7e0eef682ed7d42e23606bfce01cdc) | 2024-02-21 | 0 | {'name': 'Junctions: Graduate Journal of the Humanities'} | {'id': 'ad439cd7-5bd3-4d03-a3e4-17167ef8fb89', 'name': 'Junctions: Graduate Journal of the Humanities', 'type': 'journal', 'alternate\_names': ['Junction Grad J Humanit'], 'issn': '2468-8282', 'url': 'https://junctionsjournal.org/'} | - - - - - - + + + + + + + + +

+

1. Search query

+ (VAMP) | (latent space simul*) | (decomposition of koopman operator) | (time-lagged autoencoder) +

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2. Latent Space Simulator articles and citations over time

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+

+ +

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3. Most cited articles on Latent Space Simulator

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
TitlePublicationDate#CitationsJournal/ConferencepublicationVenue
Denoising Diffusion Implicit Models2020-10-062519ArXivInternational Conference on Learning Representations
GTM: The Generative Topographic MappingNone1496Neural ComputationNeural Computation
A Data–Driven Approximation of the Koopman Operator: Extending Dynamic Mode Decomposition2014-08-191323Journal of Nonlinear ScienceJournal of nonlinear science
Deep Autoencoding Gaussian Mixture Model for Unsupervised Anomaly Detection2018-02-151237International Conference on Learning Representations
Botulinum neurotoxin A selectively cleaves the synaptic protein SNAP-251993-09-091165NatureNature
Poincaré Embeddings for Learning Hierarchical Representations2017-05-221031ArXivNeural Information Processing Systems
Validation of information recorded on general practitioner based computerised data resource in the United Kingdom.1991-03-30877British Medical JournalBritish medical journal
Cross-domain sentiment classification via spectral feature alignment2010-04-26792{'pages': '751-760'}The Web Conference
Synaptic vesicle membrane fusion complex: action of clostridial neurotoxins on assembly.1994-11-01783The EMBO JournalEMBO Journal
VBF: Vector-Based Forwarding Protocol for Underwater Sensor Networks2006-05-15732{'pages': '1216-1221'}NA
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4. Latest articles on Latent Space Simulator

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
TitlePublicationDate#CitationsJournal/ConferencepublicationVenue
Topic Modeling on Document Networks With Dirichlet Optimal Transport Barycenter2024-03-010IEEE Transactions on Knowledge and Data EngineeringIEEE Transactions on Knowledge and Data Engineering
Multiclass and Multilabel Classifications by Consensus and Complementarity-Based Multiview Latent Space Projection2024-03-010IEEE Transactions on Systems, Man, and Cybernetics: SystemsNA
Learning-Based Edge-Device Collaborative DNN Inference in IoVT Networks2024-03-010IEEE Internet of Things JournalIEEE Internet of Things Journal
NeuralFloors: Conditional Street-Level Scene Generation From BEV Semantic Maps via Neural Fields2024-03-010IEEE Robotics and Automation LettersIEEE Robotics and Automation Letters
Robust Three-Stage Dynamic Mode Decomposition for Analysis of Power System Oscillations2024-03-010IEEE Transactions on Power SystemsIEEE Transactions on Power Systems
Vibration-based structural damage localization through a discriminant analysis strategy with cepstral coefficients2024-02-280Structural Health MonitoringStructural Health Monitoring
Spectral Time-Varying Pattern Causality and Its Application.2024-02-280IEEE journal of biomedical and health informaticsIEEE journal of biomedical and health informatics
Big topic modeling based on a two-level hierarchical latent Beta-Liouville allocation for large-scale data and parameter streaming2024-02-280Pattern Analysis and ApplicationsPattern Analysis and Applications
Sensor based Dance Coherent Action Generation Model using Deep Learning Framework2024-02-240Scalable Computing: Practice and ExperienceNA
Monstrous Mushrooms, Toxic Love and Queer Utopias in Jenny Hval's Paradise Rot2024-02-210Junctions: Graduate Journal of the HumanitiesJunctions: Graduate Journal of the Humanities
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+ + + + + \ No newline at end of file diff --git a/docs/Neural_ODEs.md b/docs/Neural_ODEs.md index 638ea7e8..7874f28d 100644 --- a/docs/Neural_ODEs.md +++ b/docs/Neural_ODEs.md @@ -2,72 +2,898 @@ hide: - navigation --- - - - - - - - -### 1. Search query - - -*(neural ordinary differential equation) | (neural ODE) | (graph neural differential equation) | (graph neural diffusion) | (graph neural ODEs)* - - - - -### 2. Neural ODEs articles and citations over time - - -![Neural ODEs](assets/Neural_ODEs.png) - - - - -### 3. Most cited articles on Neural ODEs - - - - -| Title | PublicationDate | #Citations | Journal/Conference | publicationVenue | -| --- | --- | --- | --- | --- | -| [Neural Ordinary Differential Equations](https://www.semanticscholar.org/paper/449310e3538b08b43227d660227dfd2875c3c3c1) | 2018-06-19 | 3515 | {'pages': '6572-6583'} | {'id': 'd9720b90-d60b-48bc-9df8-87a30b9a60dd', 'name': 'Neural Information Processing Systems', 'type': 'conference', 'alternate\_names': ['Neural Inf Process Syst', 'NeurIPS', 'NIPS'], 'url': 'http://neurips.cc/'} | -| [Score-Based Generative Modeling through Stochastic Differential Equations](https://www.semanticscholar.org/paper/633e2fbfc0b21e959a244100937c5853afca4853) | 2020-11-26 | 2596 | {'name': 'ArXiv', 'volume': 'abs/2011.13456'} | {'id': '939c6e1d-0d17-4d6e-8a82-66d960df0e40', 'name': 'International Conference on Learning Representations', 'type': 'conference', 'alternate\_names': ['Int Conf Learn Represent', 'ICLR'], 'url': 'https://iclr.cc/'} | -| [Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting](https://www.semanticscholar.org/paper/9ba0186ed40656329c421f55ada7313293e13f17) | 2017-07-06 | 2119 | {'name': 'arXiv: Learning', 'volume': ''} | {'id': '939c6e1d-0d17-4d6e-8a82-66d960df0e40', 'name': 'International Conference on Learning Representations', 'type': 'conference', 'alternate\_names': ['Int Conf Learn Represent', 'ICLR'], 'url': 'https://iclr.cc/'} | -| [Artificial neural networks for solving ordinary and partial differential equations](https://www.semanticscholar.org/paper/5ebbe0b1a3d7a2431bbb25d6dfeec7ed6954d633) | 1997-05-19 | 1720 | {'name': 'IEEE transactions on neural networks', 'pages': '\n 987-1000\n ', 'volume': '9 5'} | None | -| [Diffusion-Convolutional Neural Networks](https://www.semanticscholar.org/paper/18b47b83a373f33d6b902a3615f42c10f7600d72) | 2015-11-06 | 1082 | {'pages': '1993-2001'} | {'id': 'd9720b90-d60b-48bc-9df8-87a30b9a60dd', 'name': 'Neural Information Processing Systems', 'type': 'conference', 'alternate\_names': ['Neural Inf Process Syst', 'NeurIPS', 'NIPS'], 'url': 'http://neurips.cc/'} | -| [Dynamic Edge-Conditioned Filters in Convolutional Neural Networks on Graphs](https://www.semanticscholar.org/paper/1a39bb2caa151d15efd6718f3a80d9f4bff95af2) | 2017-04-10 | 1071 | {'name': '2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)', 'pages': '29-38'} | {'id': '768b87bb-8a18-4d9c-a161-4d483c776bcf', 'name': 'Computer Vision and Pattern Recognition', 'type': 'conference', 'alternate\_names': ['CVPR', 'Comput Vis Pattern Recognit'], 'issn': '1063-6919', 'url': 'https://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000147', 'alternate\_urls': ['https://en.wikipedia.org/wiki/Conference\_on\_Computer\_Vision\_and\_Pattern\_Recognition']} | -| [FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative Models](https://www.semanticscholar.org/paper/8afa6dd9f9ac46462a1fb70a757c4ae1cd45bbf6) | 2018-09-27 | 688 | {'name': 'ArXiv', 'volume': 'abs/1810.01367'} | {'id': '939c6e1d-0d17-4d6e-8a82-66d960df0e40', 'name': 'International Conference on Learning Representations', 'type': 'conference', 'alternate\_names': ['Int Conf Learn Represent', 'ICLR'], 'url': 'https://iclr.cc/'} | -| [Stable architectures for deep neural networks](https://www.semanticscholar.org/paper/37be889f4654312109dc9c53395fe117adb0f72b) | 2017-05-09 | 591 | {'name': 'Inverse Problems', 'volume': '34'} | {'id': '1901e811-ee72-4b20-8f7e-de08cd395a10', 'name': 'arXiv.org', 'alternate\_names': ['ArXiv'], 'issn': '2331-8422', 'url': 'https://arxiv.org'} | -| [Brian: A Simulator for Spiking Neural Networks in Python](https://www.semanticscholar.org/paper/aac882f968b720785613673508e7783f0efd7182) | 2008-07-11 | 526 | {'name': 'Frontiers in Neuroinformatics', 'volume': '2'} | {'id': '8eabe4e5-3d91-4297-ab8f-475904598d30', 'name': 'BMC Neuroscience', 'type': 'journal', 'alternate\_names': ['BMC Neurosci'], 'issn': '1471-2202', 'url': 'http://www.biomedcentral.com/bmcneurosci/', 'alternate\_urls': ['https://bmcneurosci.biomedcentral.com/', 'http://www.pubmedcentral.nih.gov/tocrender.fcgi?journal=49', 'http://www.biomedcentral.com/bmcneurosci/archive/']} | -| [DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps](https://www.semanticscholar.org/paper/4530c25da949bb2185c50663158ef19d52e3c6b5) | 2022-06-02 | 495 | {'name': 'ArXiv', 'volume': 'abs/2206.00927'} | {'id': 'd9720b90-d60b-48bc-9df8-87a30b9a60dd', 'name': 'Neural Information Processing Systems', 'type': 'conference', 'alternate\_names': ['Neural Inf Process Syst', 'NeurIPS', 'NIPS'], 'url': 'http://neurips.cc/'} | - - - - - - -### 4. Latest articles on Neural ODEs - - - - -| Title | PublicationDate | #Citations | Journal/Conference | publicationVenue | -| --- | --- | --- | --- | --- | -| [Continuous Image Outpainting with Neural ODE](https://www.semanticscholar.org/paper/2566d035a3d7f12df59b7053a610fbd54161562b) | 2024-03-02 | 0 | {'name': 'SSRN Electronic Journal'} | {'id': '75d7a8c1-d871-42db-a8e4-7cf5146fdb62', 'name': 'Social Science Research Network', 'type': 'journal', 'alternate\_names': ['SSRN, Social Science Research Network (SSRN) home page', 'SSRN Electronic Journal', 'Soc Sci Res Netw', 'SSRN', 'SSRN Home Page', 'SSRN Electron J', 'Social Science Electronic Publishing presents Social Science Research Network'], 'issn': '1556-5068', 'url': 'http://www.ssrn.com/', 'alternate\_urls': ['www.ssrn.com/', 'https://fatcat.wiki/container/tol7woxlqjeg5bmzadeg6qrg3e', 'https://www.wikidata.org/wiki/Q53949192', 'www.ssrn.com/en', 'http://www.ssrn.com/en/', 'http://umlib.nl/ssrn', 'umlib.nl/ssrn']} | -| [Graph Convolutional Neural Networks for Automated Echocardiography View Recognition: A Holistic Approach](https://www.semanticscholar.org/paper/3779b87d10925ca2bf96c3b8b971330c8682e06e) | 2024-02-29 | 0 | {'pages': '44-54'} | None | -| [Modelling and Distribution of Electricity Load Forecasting in Nigeria Power System (Olu-Ode Community)](https://www.semanticscholar.org/paper/77308f9484b9c372ad028e04301c07f5e92c566b) | 2024-02-28 | 0 | {'name': 'International Journal of Advanced Engineering and Nano Technology'} | {'id': 'b2a6f6aa-b866-4069-8e96-b765cd7776f9', 'name': 'International Journal of Advanced Engineering and Nano Technology', 'type': 'journal', 'alternate\_names': ['Int J Adv Eng Nano Technol'], 'issn': '2347-6389', 'url': 'https://www.ijaent.org/'} | -| [Changes in Structural Neural Networks in the Recovery Process of Motor Paralysis after Stroke](https://www.semanticscholar.org/paper/93a3bdec5c232a639d5cd0be5f7cb430caafdd2f) | 2024-02-21 | 0 | {'name': 'Brain Sciences'} | {'id': '39058e09-c13a-4545-a8a3-a75581460bc2', 'name': 'Brain Science', 'type': 'journal', 'alternate\_names': ['Brain Sciences', 'Brain Sci'], 'issn': '2570-0197', 'alternate\_issns': ['2076-3425'], 'url': 'http://www.e-helvetica.nb.admin.ch/directAccess?callnumber=bel-217894', 'alternate\_urls': ['https://www.mdpi.com/journal/brainsci', 'https://epub.uni-regensburg.de/37319/', 'http://nbn-resolving.de/urn/resolver.pl?urn=urn:nbn:ch:bel-217894']} | -| [Zhang neural networks: an introduction to predictive computations for discretized time-varying matrix problems](https://www.semanticscholar.org/paper/d9b9e3efbe9528468442ca216a59223847d31fa4) | 2024-02-19 | 0 | {'name': 'Numerische Mathematik'} | {'id': '23ed2049-ad4e-4e12-8e48-a4e55bc4e377', 'name': 'Numerische Mathematik', 'type': 'journal', 'alternate\_names': ['Numer Math'], 'issn': '0029-599X', 'url': 'http://www.springer.com/mathematics/numerical+and+computational+mathematics/journal/211', 'alternate\_urls': ['http://www.digizeitschriften.de/main/dms/toc/?PPN=PPN362160546', 'https://link.springer.com/journal/211']} | -| [Emulating the interstellar medium chemistry with neural operators](https://www.semanticscholar.org/paper/5005529d4850a80e2234177e2a2625ed7ac60a68) | 2024-02-19 | 0 | {'name': 'Astronomy & Astrophysics'} | None | -| [Temporal Disentangled Contrastive Diffusion Model for Spatiotemporal Imputation](https://www.semanticscholar.org/paper/94e459909290d427dffaee3052a19ed32300b89a) | 2024-02-18 | 0 | {'name': 'ArXiv', 'volume': 'abs/2402.11558'} | {'id': '1901e811-ee72-4b20-8f7e-de08cd395a10', 'name': 'arXiv.org', 'alternate\_names': ['ArXiv'], 'issn': '2331-8422', 'url': 'https://arxiv.org'} | -| [Uncertainty Quantification of Graph Convolution Neural Network Models of Evolving Processes](https://www.semanticscholar.org/paper/3e64d1ecf181a7115d7f4a61834f1e7e7defc6bf) | 2024-02-17 | 0 | {'name': 'ArXiv', 'volume': 'abs/2402.11179'} | {'id': '1901e811-ee72-4b20-8f7e-de08cd395a10', 'name': 'arXiv.org', 'alternate\_names': ['ArXiv'], 'issn': '2331-8422', 'url': 'https://arxiv.org'} | -| [ContiFormer: Continuous-Time Transformer for Irregular Time Series Modeling](https://www.semanticscholar.org/paper/5ee2008c1eab4545f1e001b2cf3c0578b7a1aafe) | 2024-02-16 | 1 | {'name': 'ArXiv', 'volume': 'abs/2402.10635'} | {'id': 'd9720b90-d60b-48bc-9df8-87a30b9a60dd', 'name': 'Neural Information Processing Systems', 'type': 'conference', 'alternate\_names': ['Neural Inf Process Syst', 'NeurIPS', 'NIPS'], 'url': 'http://neurips.cc/'} | -| [Beyond Kalman Filters: Deep Learning-Based Filters for Improved Object Tracking](https://www.semanticscholar.org/paper/dfb10dec07e4e45faec83014d0c6764bd5a0a588) | 2024-02-15 | 0 | {'name': 'ArXiv', 'volume': 'abs/2402.09865'} | {'id': '1901e811-ee72-4b20-8f7e-de08cd395a10', 'name': 'arXiv.org', 'alternate\_names': ['ArXiv'], 'issn': '2331-8422', 'url': 'https://arxiv.org'} | - - - - - - + + + + + + + + +

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Table of Contents

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  • 1. Search Query
    • +
  • 2. Neural ODEs articles and citations over time
    • +
  • 3. Most cited articles on Neural ODEs
    • +
  • 4. Latest articles on Neural ODEs
    • +

    + +

    +

    1. Search query

    + (neural ordinary differential equation) | (neural ODE) | (graph neural differential equation) | (graph neural diffusion) | (graph neural ODEs) +

    + +

    +

    2. Neural ODEs articles and citations over time

    +
    + +
    +

    + +

    +

    3. Most cited articles on Neural ODEs

    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    TitlePublicationDate#CitationsJournal/ConferencepublicationVenue
    Neural Ordinary Differential Equations2018-06-193517{'pages': '6572-6583'}Neural Information Processing Systems
    Score-Based Generative Modeling through Stochastic Differential Equations2020-11-262600ArXivInternational Conference on Learning Representations
    Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting2017-07-062120arXiv: LearningInternational Conference on Learning Representations
    Artificial neural networks for solving ordinary and partial differential equations1997-05-191721IEEE transactions on neural networksNA
    Diffusion-Convolutional Neural Networks2015-11-061084{'pages': '1993-2001'}Neural Information Processing Systems
    Dynamic Edge-Conditioned Filters in Convolutional Neural Networks on Graphs2017-04-1010712017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)Computer Vision and Pattern Recognition
    FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative Models2018-09-27688ArXivInternational Conference on Learning Representations
    Stable architectures for deep neural networks2017-05-09591Inverse ProblemsarXiv.org
    Brian: A Simulator for Spiking Neural Networks in Python2008-07-11526Frontiers in NeuroinformaticsBMC Neuroscience
    DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps2022-06-02494ArXivNeural Information Processing Systems
    Augmented Neural ODEs2019-04-02492ArXivNeural Information Processing Systems
    Diffusion Improves Graph Learning2019-10-28486{'pages': '13333-13345'}Neural Information Processing Systems
    Geometric Matrix Completion with Recurrent Multi-Graph Neural Networks2017-04-01465{'pages': '3697-3707'}Neural Information Processing Systems
    Neural Operator: Graph Kernel Network for Partial Differential Equations2020-02-26443ArXivInternational Conference on Learning Representations
    Simulation of chaotic EEG patterns with a dynamic model of the olfactory system1987-05-01439Biological CyberneticsBiological cybernetics
    Beyond Finite Layer Neural Networks: Bridging Deep Architectures and Numerical Differential Equations2017-10-27429ArXivInternational Conference on Machine Learning
    Latent Ordinary Differential Equations for Irregularly-Sampled Time SeriesNone409{'pages': '5321-5331'}Neural Information Processing Systems
    Adaptive NN Backstepping Output-Feedback Control for Stochastic Nonlinear Strict-Feedback Systems With Time-Varying Delays2010-06-01403IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics)NA
    Rumor Detection on Social Media with Bi-Directional Graph Convolutional Networks2020-01-17379{'pages': '549-556'}AAAI Conference on Artificial Intelligence
    A Deep Collocation Method for the Bending Analysis of Kirchhoff Plate2021-02-04365ArXivComputers Materials & Continua
    Decoupling dynamical systems for pathway identification from metabolic profiles2004-07-22317BioinformaticsNA
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    4. Latest articles on Neural ODEs

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    Approximation of Solution Operators for High-dimensional PDEs2024-01-180ArXivarXiv.org
    Port-Hamiltonian Neural ODE Networks on Lie Groups For Robot Dynamics Learning and Control2024-01-170ArXivarXiv.org
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    + + + + + \ No newline at end of file diff --git a/docs/PINNs.md b/docs/PINNs.md index 8cff4265..26919795 100644 --- a/docs/PINNs.md +++ b/docs/PINNs.md @@ -2,72 +2,256 @@ hide: - navigation --- - - - - - - - -### 1. Search query - - -*(physics-informed neural computing)* - - - - -### 2. PINNs articles and citations over time - - -![PINNs](assets/PINNs.png) - - - - -### 3. Most cited articles on PINNs - - - - -| Title | PublicationDate | #Citations | Journal/Conference | publicationVenue | -| --- | --- | --- | --- | --- | -| [Physics-informed learning of governing equations from scarce data](https://www.semanticscholar.org/paper/e596988b1df3a0bc78bf72c0bfdb21c85eaab6c9) | 2020-05-05 | 177 | {'name': 'Nature Communications', 'volume': '12'} | {'id': '43b3f0f9-489a-4566-8164-02fafde3cd98', 'name': 'Nature Communications', 'type': 'journal', 'alternate\_names': ['Nat Commun'], 'issn': '2041-1723', 'url': 'https://www.nature.com/ncomms/', 'alternate\_urls': ['http://www.nature.com/ncomms/about/index.html', 'http://www.nature.com/ncomms/index.html']} | -| [Learning in Modal Space: Solving Time-Dependent Stochastic PDEs Using Physics-Informed Neural Networks](https://www.semanticscholar.org/paper/7fdccf0d550e1a8db830d280bbf3e7b3e6d66653) | 2019-05-03 | 160 | {'name': 'ArXiv', 'volume': 'abs/1905.01205'} | {'id': '0e3b51a7-21d8-477c-8918-14a55f087532', 'name': 'SIAM Journal on Scientific Computing', 'type': 'journal', 'alternate\_names': ['SIAM J Sci Comput'], 'issn': '1064-8275', 'url': 'http://www.siam.org/journals/sisc.php', 'alternate\_urls': ['https://epubs.siam.org/journal/sjoce3']} | -| [Efficient training of physics‐informed neural networks via importance sampling](https://www.semanticscholar.org/paper/af68d37e2721abe702bacfcea5111f9ec59012ce) | 2021-04-26 | 113 | {'name': 'Computer‐Aided Civil and Infrastructure Engineering', 'pages': '962 - 977', 'volume': '36'} | None | -| [The Old and the New: Can Physics-Informed Deep-Learning Replace Traditional Linear Solvers?](https://www.semanticscholar.org/paper/1a0db1672f4d08a81b02fd35453d5d04d3013635) | 2021-03-12 | 109 | {'name': 'Frontiers in Big Data', 'volume': '4'} | {'id': '165fa1b5-e07f-4b6e-9203-04493f6a7c5c', 'name': 'Frontiers in Big Data', 'alternate\_names': ['Front Big Data'], 'issn': '2624-909X', 'url': 'https://www.frontiersin.org/journals/big-data'} | -| [ClimaX: A foundation model for weather and climate](https://www.semanticscholar.org/paper/874deb5f06f35e52ae13a921b23611eec4abd1da) | 2023-01-24 | 87 | {'pages': '25904-25938'} | {'id': 'fc0a208c-acb7-47dc-a0d4-af8190e21d29', 'name': 'International Conference on Machine Learning', 'type': 'conference', 'alternate\_names': ['ICML', 'Int Conf Mach Learn'], 'url': 'https://icml.cc/'} | -| [A Physics-Informed Neural Network for Quantifying the Microstructural Properties of Polycrystalline Nickel Using Ultrasound Data: A promising approach for solving inverse problems](https://www.semanticscholar.org/paper/bde6492eb852a10ffd4bba5d7df23e37f9b81a3e) | 2021-03-25 | 52 | {'name': 'IEEE Signal Processing Magazine', 'pages': '68-77', 'volume': '39'} | {'id': 'f62e5eab-173a-4e0a-a963-ed8de9835d22', 'name': 'IEEE Signal Processing Magazine', 'type': 'journal', 'alternate\_names': ['IEEE Signal Process Mag'], 'issn': '1053-5888', 'url': 'http://ieeexplore.ieee.org/servlet/opac?punumber=79', 'alternate\_urls': ['https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=79']} | -| [NeuralPDE: Automating Physics-Informed Neural Networks (PINNs) with Error Approximations](https://www.semanticscholar.org/paper/e15133cfd09c2a2eb98c38468a897866a904d125) | 2021-07-19 | 44 | {'name': 'ArXiv', 'volume': 'abs/2107.09443'} | {'id': '1901e811-ee72-4b20-8f7e-de08cd395a10', 'name': 'arXiv.org', 'alternate\_names': ['ArXiv'], 'issn': '2331-8422', 'url': 'https://arxiv.org'} | -| [A comparative study of physics-informed neural network models for learning unknown dynamics and constitutive relations](https://www.semanticscholar.org/paper/373a6cb7cf455191a81cd16649e0a02ecb558e7a) | 2019-04-02 | 33 | {'name': 'ArXiv', 'volume': 'abs/1904.04058'} | {'id': '1901e811-ee72-4b20-8f7e-de08cd395a10', 'name': 'arXiv.org', 'alternate\_names': ['ArXiv'], 'issn': '2331-8422', 'url': 'https://arxiv.org'} | -| [A novel meta-learning initialization method for physics-informed neural networks](https://www.semanticscholar.org/paper/d6be8e09ed6c47e8b5c459ef4bab1015afb01973) | 2021-07-23 | 32 | {'name': 'Neural Computing and Applications', 'pages': '14511 - 14534', 'volume': '34'} | None | -| [Identification and prediction of time-varying parameters of COVID-19 model: a data-driven deep learning approach](https://www.semanticscholar.org/paper/387f4a128f84ddd9ce7fa530711dd7918b037978) | 2021-03-17 | 31 | {'name': 'International Journal of Computer Mathematics', 'pages': '1617 - 1632', 'volume': '98'} | {'id': '0815ec9f-1740-4242-ab39-5e71b6d57346', 'name': 'International Journal of Computational Mathematics', 'type': 'journal', 'alternate\_names': ['International Journal of Computer-Generated Mathematics', 'Int J Comput Math', 'International Journal of Computer Mathematics'], 'issn': '2314-856X', 'alternate\_issns': ['0020-7160', '2367-6493'], 'url': 'https://www.hindawi.com/journals/ijcm/', 'alternate\_urls': ['http://www.tandf.co.uk/journals/default.asp', 'http://www.ddekov.eu/j/', 'http://www.tandfonline.com/loi/gcom20']} | - - - - - - -### 4. Latest articles on PINNs - - - - -| Title | PublicationDate | #Citations | Journal/Conference | publicationVenue | -| --- | --- | --- | --- | --- | -| [New insights into experimental stratified flows obtained through physics-informed neural networks](https://www.semanticscholar.org/paper/55f66c4639902b7bdca1ec3db18e08cf98bcd301) | 2024-02-23 | 0 | {'name': 'Journal of Fluid Mechanics'} | {'id': 'fb1aca4e-2d42-48af-83dc-f5b1a3651a36', 'name': 'Journal of Fluid Mechanics', 'type': 'journal', 'alternate\_names': ['J Fluid Mech'], 'issn': '0022-1120', 'url': 'https://www.cambridge.org/core/journals/journal-of-fluid-mechanics', 'alternate\_urls': ['http://journals.cambridge.org/action/displayJournal?jid=FLM', 'http://www.journals.cambridge.org/bin/bladerunner?30REQEVENT=&500002REQSUB=&REQAUTH=0&REQSTR1=JournalofFluidMechanics']} | -| [Regression Transients Modeling of Solid Rocket Motor Burning Surfaces with Physics-guided Neural Network](https://www.semanticscholar.org/paper/043675aed01841c86c684457b8e88066f6094bc3) | 2024-02-14 | 0 | {'name': 'Machine Learning: Science and Technology'} | None | -| [Energy-based PINNs for solving coupled field problems: concepts and application to the optimal design of an induction heater](https://www.semanticscholar.org/paper/6620d79b3603639d1a1d4054de4e09c2c977b7f0) | 2024-02-09 | 0 | {'name': 'ArXiv', 'volume': 'abs/2402.06261'} | {'id': '1901e811-ee72-4b20-8f7e-de08cd395a10', 'name': 'arXiv.org', 'alternate\_names': ['ArXiv'], 'issn': '2331-8422', 'url': 'https://arxiv.org'} | -| [Enriched Physics-informed Neural Networks for Dynamic Poisson-Nernst-Planck Systems](https://www.semanticscholar.org/paper/bc3d14c809e0a8da182bcb2f30797c5edaa3fd48) | 2024-02-01 | 0 | {'name': 'ArXiv', 'volume': 'abs/2402.01768'} | {'id': '1901e811-ee72-4b20-8f7e-de08cd395a10', 'name': 'arXiv.org', 'alternate\_names': ['ArXiv'], 'issn': '2331-8422', 'url': 'https://arxiv.org'} | -| [Physics-informed neural networks with domain decomposition for the incompressible Navier–Stokes equations](https://www.semanticscholar.org/paper/6ab365eb128bf97c7779805806184c8d2a0f0ec1) | 2024-02-01 | 0 | {'name': 'Physics of Fluids'} | {'id': 'fcb86ed6-f18e-4059-9779-7acc73d8b8ab', 'name': 'The Physics of Fluids', 'type': 'journal', 'alternate\_names': ['Physics of Fluids', 'Phys Fluid'], 'issn': '0031-9171', 'alternate\_issns': ['1070-6631'], 'url': 'https://aip.scitation.org/journal/phf', 'alternate\_urls': ['http://pof.aip.org/']} | -| [Adaptive Deep Fourier Residual method via overlapping domain decomposition](https://www.semanticscholar.org/paper/ba5b00d09b5cb44c3b59d86e4cf051430f984474) | 2024-01-09 | 0 | {'name': 'ArXiv', 'volume': 'abs/2401.04663'} | {'id': '1901e811-ee72-4b20-8f7e-de08cd395a10', 'name': 'arXiv.org', 'alternate\_names': ['ArXiv'], 'issn': '2331-8422', 'url': 'https://arxiv.org'} | -| [Computing the Gerber-Shiu function with interest and a constant dividend barrier by physics-informed neural networks](https://www.semanticscholar.org/paper/a852a6c427fcbffcad2a3c4f179d9a82cbdbef47) | 2024-01-09 | 0 | {'name': 'ArXiv', 'volume': 'abs/2401.04378'} | {'id': '1901e811-ee72-4b20-8f7e-de08cd395a10', 'name': 'arXiv.org', 'alternate\_names': ['ArXiv'], 'issn': '2331-8422', 'url': 'https://arxiv.org'} | -| [Modeling multisource multifrequency acoustic wavefields by a multiscale Fourier feature physics-informed neural network with adaptive activation functions](https://www.semanticscholar.org/paper/27b4ccd8fef1d27856300460ecc7fbfdd0e73c81) | 2024-01-09 | 0 | {'name': 'GEOPHYSICS'} | {'id': '74f68976-b242-4148-9315-8fd8095a9ecd', 'name': 'Geophysics', 'type': 'journal', 'issn': '0016-8033', 'url': 'http://www.geo-online.org/', 'alternate\_urls': ['https://library.seg.org/journal/gpysa7']} | -| [Physics-Guided, Physics-Informed, and Physics-Encoded Neural Networks and Operators in Scientific Computing: Fluid and Solid Mechanics](https://www.semanticscholar.org/paper/bc9ae66c84e31839015dd30c0bd76548bf1b7a5c) | 2024-01-08 | 4 | {'name': 'Journal of Computing and Information Science in Engineering'} | {'id': 'd029f971-f74c-41ca-8373-1b713414c797', 'name': 'Journal of Computing and Information Science in Engineering', 'type': 'journal', 'alternate\_names': ['J Comput Inf Sci Eng'], 'issn': '1530-9827', 'url': 'https://www.asme.org/', 'alternate\_urls': ['http://computingengineering.asmedigitalcollection.asme.org/journal.aspx?journalid=116', 'http://computingengineering.asmedigitalcollection.asme.org/', 'http://computingengineering.asmedigitalcollection.asme.org/journal.aspx']} | -| [Solving real-world optimization tasks using physics-informed neural computing](https://www.semanticscholar.org/paper/23c7b93a379c26c3738921282771e1a545538703) | 2024-01-08 | 1 | {'name': 'Scientific Reports', 'volume': '14'} | {'id': 'f99f77b7-b1b6-44d3-984a-f288e9884b9b', 'name': 'Scientific Reports', 'type': 'journal', 'alternate\_names': ['Sci Rep'], 'issn': '2045-2322', 'url': 'http://www.nature.com/srep/', 'alternate\_urls': ['http://www.nature.com/srep/index.html']} | - - - - - - + + + + + + + + + +

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    1. Search query

    + (physics-informed neural computing) +

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    2. PINNs articles and citations over time

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    3. Most cited articles on PINNs

    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    TitlePublicationDate#CitationsJournal/ConferencepublicationVenue
    Physics-informed learning of governing equations from scarce data2020-05-05177Nature CommunicationsNature Communications
    Learning in Modal Space: Solving Time-Dependent Stochastic PDEs Using Physics-Informed Neural Networks2019-05-03160ArXivSIAM Journal on Scientific Computing
    Efficient training of physics‐informed neural networks via importance sampling2021-04-26113Computer‐Aided Civil and Infrastructure EngineeringNA
    The Old and the New: Can Physics-Informed Deep-Learning Replace Traditional Linear Solvers?2021-03-12109Frontiers in Big DataFrontiers in Big Data
    ClimaX: A foundation model for weather and climate2023-01-2487{'pages': '25904-25938'}International Conference on Machine Learning
    A Physics-Informed Neural Network for Quantifying the Microstructural Properties of Polycrystalline Nickel Using Ultrasound Data: A promising approach for solving inverse problems2021-03-2552IEEE Signal Processing MagazineIEEE Signal Processing Magazine
    NeuralPDE: Automating Physics-Informed Neural Networks (PINNs) with Error Approximations2021-07-1944ArXivarXiv.org
    A comparative study of physics-informed neural network models for learning unknown dynamics and constitutive relations2019-04-0233ArXivarXiv.org
    A novel meta-learning initialization method for physics-informed neural networks2021-07-2332Neural Computing and ApplicationsNA
    Identification and prediction of time-varying parameters of COVID-19 model: a data-driven deep learning approach2021-03-1731International Journal of Computer MathematicsInternational Journal of Computational Mathematics
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    4. Latest articles on PINNs

    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    TitlePublicationDate#CitationsJournal/ConferencepublicationVenue
    New insights into experimental stratified flows obtained through physics-informed neural networks2024-02-230Journal of Fluid MechanicsJournal of Fluid Mechanics
    Regression Transients Modeling of Solid Rocket Motor Burning Surfaces with Physics-guided Neural Network2024-02-140Machine Learning: Science and TechnologyNA
    Energy-based PINNs for solving coupled field problems: concepts and application to the optimal design of an induction heater2024-02-090ArXivarXiv.org
    Enriched Physics-informed Neural Networks for Dynamic Poisson-Nernst-Planck Systems2024-02-010ArXivarXiv.org
    Physics-informed neural networks with domain decomposition for the incompressible Navier–Stokes equations2024-02-010Physics of FluidsThe Physics of Fluids
    Adaptive Deep Fourier Residual method via overlapping domain decomposition2024-01-090ArXivarXiv.org
    Computing the Gerber-Shiu function with interest and a constant dividend barrier by physics-informed neural networks2024-01-090ArXivarXiv.org
    Modeling multisource multifrequency acoustic wavefields by a multiscale Fourier feature physics-informed neural network with adaptive activation functions2024-01-090GEOPHYSICSGeophysics
    Physics-Guided, Physics-Informed, and Physics-Encoded Neural Networks and Operators in Scientific Computing: Fluid and Solid Mechanics2024-01-084Journal of Computing and Information Science in EngineeringJournal of Computing and Information Science in Engineering
    Solving real-world optimization tasks using physics-informed neural computing2024-01-081Scientific ReportsScientific Reports
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    + + + + + \ No newline at end of file diff --git a/docs/Physics-informed_GNNs.md b/docs/Physics-informed_GNNs.md index 694cc908..38d4f44c 100644 --- a/docs/Physics-informed_GNNs.md +++ b/docs/Physics-informed_GNNs.md @@ -2,72 +2,898 @@ hide: - navigation --- - - - - - - - -### 1. Search query - - -*(graph networks) | (physics constrain) | (learned simulator) | (learned simulation)* - - - - -### 2. Physics-informed GNNs articles and citations over time - - -![Physics-informed GNNs](assets/Physics-informed_GNNs.png) - - - - -### 3. Most cited articles on Physics-informed GNNs - - - - -| Title | PublicationDate | #Citations | Journal/Conference | publicationVenue | -| --- | --- | --- | --- | --- | -| [Gradient-based learning applied to document recognition](https://www.semanticscholar.org/paper/162d958ff885f1462aeda91cd72582323fd6a1f4) | None | 46003 | {'name': 'Proc. IEEE', 'pages': '2278-2324', 'volume': '86'} | {'id': '6faaccca-1cc4-45a9-aeb6-96a4901d2606', 'name': 'Proceedings of the IEEE', 'type': 'journal', 'alternate\_names': ['Proc IEEE'], 'issn': '0018-9219', 'alternate\_issns': ['1558-2256'], 'url': 'http://www.ieee.org/portal/pages/pubs/proceedings/', 'alternate\_urls': ['http://www.ieee.org/products/onlinepubs/pub/about\_conference.html', 'https://ieeexplore.ieee.org/servlet/opac?punumber=5', 'http://proceedingsoftheieee.ieee.org/']} | -| [Collective dynamics of ‘small-world’ networks](https://www.semanticscholar.org/paper/d61031326150ba23f90e6587c13d99188209250e) | 1998-06-04 | 38484 | {'name': 'Nature', 'pages': '440-442', 'volume': '393'} | {'id': '6c24a0a0-b07d-4d7b-a19b-fd09a3ed453a', 'name': 'Nature', 'type': 'journal', 'issn': '0028-0836', 'url': 'https://www.nature.com/', 'alternate\_urls': ['http://www.nature.com/nature/', 'https://www.nature.com/nature/', 'http://www.nature.com/nature/archive/index.html']} | -| [Semi-Supervised Classification with Graph Convolutional Networks](https://www.semanticscholar.org/paper/36eff562f65125511b5dfab68ce7f7a943c27478) | 2016-09-09 | 22114 | {'name': 'ArXiv', 'volume': 'abs/1609.02907'} | {'id': '939c6e1d-0d17-4d6e-8a82-66d960df0e40', 'name': 'International Conference on Learning Representations', 'type': 'conference', 'alternate\_names': ['Int Conf Learn Represent', 'ICLR'], 'url': 'https://iclr.cc/'} | -| [Statistical mechanics of complex networks](https://www.semanticscholar.org/paper/dce8146987557735a19771aefa1f027211a2c275) | 2001-06-06 | 18824 | {'name': 'ArXiv', 'volume': 'cond-mat/0106096'} | {'id': '1901e811-ee72-4b20-8f7e-de08cd395a10', 'name': 'arXiv.org', 'alternate\_names': ['ArXiv'], 'issn': '2331-8422', 'url': 'https://arxiv.org'} | -| [The Structure and Function of Complex Networks](https://www.semanticscholar.org/paper/e6c4925fb114d13a8568f88957c167c928f0c9f1) | 2003-03-25 | 16785 | {'name': 'SIAM Rev.', 'pages': '167-256', 'volume': '45'} | {'id': '8f59dd66-e4cd-4341-8ea9-9a03d965a009', 'name': 'SIAM Review', 'type': 'journal', 'alternate\_names': ['SIAM Rev', 'Siam Rev', 'Siam Review'], 'issn': '0036-1445', 'url': 'https://www.jstor.org/journal/siamreview', 'alternate\_urls': ['http://www.jstor.org/journals/00361445.html', 'https://epubs.siam.org/journal/siread', 'http://www.siam.org/journals/sirev.php']} | -| [TensorFlow: A system for large-scale machine learning](https://www.semanticscholar.org/paper/4954fa180728932959997a4768411ff9136aac81) | 2016-05-27 | 16703 | {'pages': '265-283'} | {'id': '86c43745-31d9-4c1a-b33f-ce3aa0042dbb', 'name': 'USENIX Symposium on Operating Systems Design and Implementation', 'type': 'conference', 'alternate\_names': ['Oper Syst Des Implement', 'Operating Systems Design and Implementation', 'OSDI', 'USENIX Symp Oper Syst Des Implement']} | -| [Community structure in social and biological networks](https://www.semanticscholar.org/paper/2a005868b79511cf8c924cd5990e2497527a0527) | 2001-12-07 | 14280 | {'name': 'Proceedings of the National Academy of Sciences of the United States of America', 'pages': '7821 - 7826', 'volume': '99'} | {'id': 'bb95bf2e-8383-4748-bf9d-d6906d091085', 'name': 'Proceedings of the National Academy of Sciences of the United States of America', 'type': 'journal', 'alternate\_names': ['PNAS', 'PNAS online', 'Proceedings of the National Academy of Sciences of the United States of America.', 'Proc National Acad Sci', 'Proceedings of the National Academy of Sciences', 'Proc National Acad Sci u s Am'], 'issn': '0027-8424', 'alternate\_issns': ['1091-6490'], 'url': 'https://www.jstor.org/journal/procnatiacadscie', 'alternate\_urls': ['http://www.pnas.org/', 'https://www.pnas.org/', 'http://www.jstor.org/journals/00278424.html', 'www.pnas.org/']} | -| [Graph Attention Networks](https://www.semanticscholar.org/paper/33998aff64ce51df8dee45989cdca4b6b1329ec4) | 2017-10-30 | 13972 | {'name': 'ArXiv', 'volume': 'abs/1710.10903'} | {'id': '939c6e1d-0d17-4d6e-8a82-66d960df0e40', 'name': 'International Conference on Learning Representations', 'type': 'conference', 'alternate\_names': ['Int Conf Learn Represent', 'ICLR'], 'url': 'https://iclr.cc/'} | -| [PRISMA Extension for Scoping Reviews (PRISMA-ScR): Checklist and Explanation](https://www.semanticscholar.org/paper/450106c6c960424b365249f2a301ce0abe24e346) | 2018-10-02 | 12792 | {'name': 'Annals of Internal Medicine', 'pages': '467-473', 'volume': '169'} | {'id': '643b0c17-99ac-463b-81c4-df44ad66e34d', 'name': 'Annals of Internal Medicine', 'type': 'journal', 'alternate\_names': ['Ann Intern Med'], 'issn': '0003-4819', 'url': 'http://www.acponline.org/journals/annals/annaltoc.htm', 'alternate\_urls': ['http://www.annals.org/']} | -| [Consensus problems in networks of agents with switching topology and time-delays](https://www.semanticscholar.org/paper/9839ed2281ba4b589bf88c7e4acc48c9fa6fb933) | 2004-09-13 | 11249 | {'name': 'IEEE Transactions on Automatic Control', 'pages': '1520-1533', 'volume': '49'} | {'id': '1283a59c-0d1f-48c3-81d7-02172f597e70', 'name': 'IEEE Transactions on Automatic Control', 'type': 'journal', 'alternate\_names': ['IEEE Trans Autom Control'], 'issn': '0018-9286', 'url': 'http://ieeexplore.ieee.org/servlet/opac?punumber=9'} | - - - - - - -### 4. Latest articles on Physics-informed GNNs - - - - -| Title | PublicationDate | #Citations | Journal/Conference | publicationVenue | -| --- | --- | --- | --- | --- | -| [Hierarchical spatio-temporal graph convolutional neural networks for traffic data imputation](https://www.semanticscholar.org/paper/04744b6893487a608e3726fb4542e2a7f9e81a5b) | 2024-06-01 | 0 | {'name': 'Information Fusion'} | {'id': '06afdd0b-0d85-413f-af8a-c3045c12c561', 'name': 'Information Fusion', 'type': 'journal', 'alternate\_names': ['Inf Fusion'], 'issn': '1566-2535', 'url': 'https://www.journals.elsevier.com/information-fusion', 'alternate\_urls': ['http://www.sciencedirect.com/science/journal/15662535']} | -| [Reagent dosage inference based on graph convolutional memory perception network for zinc roughing flotation](https://www.semanticscholar.org/paper/ba23319a62da63ec3b664f6452bb7a9aee8a46dc) | 2024-05-01 | 0 | {'name': 'Control Engineering Practice'} | {'id': 'af74e393-8f45-41cd-915b-734494cb48f2', 'name': 'Control Engineering Practice', 'type': 'journal', 'alternate\_names': ['Control Eng Pract'], 'issn': '0967-0661', 'url': 'http://www.elsevier.com/wps/find/journaldescription.cws\_home/123/description#description', 'alternate\_urls': ['http://www.sciencedirect.com/science/journal/09670661']} | -| [MACNS: A generic graph neural network integrated deep reinforcement learning based multi-agent collaborative navigation system for dynamic trajectory planning](https://www.semanticscholar.org/paper/a1a503c7c23502bebe94eb042b0ce9f8bdbb6504) | 2024-05-01 | 0 | {'name': 'Inf. Fusion', 'pages': '102250', 'volume': '105'} | {'id': '06afdd0b-0d85-413f-af8a-c3045c12c561', 'name': 'Information Fusion', 'type': 'journal', 'alternate\_names': ['Inf Fusion'], 'issn': '1566-2535', 'url': 'https://www.journals.elsevier.com/information-fusion', 'alternate\_urls': ['http://www.sciencedirect.com/science/journal/15662535']} | -| [DawnGNN: Documentation augmented windows malware detection using graph neural network](https://www.semanticscholar.org/paper/45cb2614652147789e18f1bc15d665977d2d1ee9) | 2024-05-01 | 0 | {'name': 'Computers & Security'} | None | -| [Multi-level Graph Memory Network Cluster Convolutional Recurrent Network for traffic forecasting](https://www.semanticscholar.org/paper/357677ec8b2223f049c45c7330633a5b85c2bc95) | 2024-05-01 | 0 | {'name': 'Inf. Fusion', 'pages': '102214', 'volume': '105'} | {'id': '06afdd0b-0d85-413f-af8a-c3045c12c561', 'name': 'Information Fusion', 'type': 'journal', 'alternate\_names': ['Inf Fusion'], 'issn': '1566-2535', 'url': 'https://www.journals.elsevier.com/information-fusion', 'alternate\_urls': ['http://www.sciencedirect.com/science/journal/15662535']} | -| [FairCare: Adversarial training of a heterogeneous graph neural network with attention mechanism to learn fair representations of electronic health records](https://www.semanticscholar.org/paper/3383c82d39b88e5349d345e32e879806bd72d435) | 2024-05-01 | 0 | {'name': 'Information Processing & Management'} | None | -| [Multi-criteria group decision making based on graph neural networks in Pythagorean fuzzy environment](https://www.semanticscholar.org/paper/13a50769f110029fcb3390956789aec236071c53) | 2024-05-01 | 1 | {'name': 'Expert Systems with Applications'} | {'id': '987139ae-a65d-49bb-aaf6-fb764dc40b19', 'name': 'Expert systems with applications', 'type': 'journal', 'alternate\_names': ['Expert syst appl', 'Expert Systems With Applications', 'Expert Syst Appl'], 'issn': '0957-4174', 'url': 'https://www.journals.elsevier.com/expert-systems-with-applications/', 'alternate\_urls': ['https://www.sciencedirect.com/journal/expert-systems-with-applications', 'http://www.sciencedirect.com/science/journal/09574174']} | -| [POI recommendation for random groups based on cooperative graph neural networks](https://www.semanticscholar.org/paper/0cfd9a1774cf41ff07e957bbc25d14596d529c4f) | 2024-05-01 | 0 | {'name': 'Information Processing & Management'} | None | -| [Attention based multi-task interpretable graph convolutional network for Alzheimer’s disease analysis](https://www.semanticscholar.org/paper/fc5ee86473fd698e3f4405b51bdfe0575304a30d) | 2024-04-01 | 0 | {'name': 'Pattern Recognition Letters'} | {'id': 'f35e3e87-9df4-497b-aa0d-bb8584197290', 'name': 'Pattern Recognition Letters', 'type': 'journal', 'alternate\_names': ['Pattern Recognit Lett'], 'issn': '0167-8655', 'url': 'https://www.journals.elsevier.com/pattern-recognition-letters/', 'alternate\_urls': ['http://www.journals.elsevier.com/pattern-recognition-letters/', 'http://www.sciencedirect.com/science/journal/01678655']} | -| [A coarse-to-fine adaptive spatial–temporal graph convolution network with residuals for motor imagery decoding from the same limb](https://www.semanticscholar.org/paper/f56be81f12e0c0bdf632d5feeaf028dfb791223a) | 2024-04-01 | 0 | {'name': 'Biomedical Signal Processing and Control'} | {'id': '1bac31b4-014a-4981-ae41-af2a40acc162', 'name': 'Biomedical Signal Processing and Control', 'type': 'journal', 'alternate\_names': ['Biomed Signal Process Control'], 'issn': '1746-8094', 'url': 'https://www.journals.elsevier.com/biomedical-signal-processing-and-control', 'alternate\_urls': ['http://www.sciencedirect.com/science/journal/17468094']} | - - - - - - + + + + + + + + +

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    Table of Contents

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  • 1. Search Query
    • +
  • 2. Physics-informed GNNs articles and citations over time
    • +
  • 3. Most cited articles on Physics-informed GNNs
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  • 4. Latest articles on Physics-informed GNNs
    • +

    + +

    +

    1. Search query

    + (graph networks) | (physics constrain) | (learned simulator) | (learned simulation) +

    + +

    +

    2. Physics-informed GNNs articles and citations over time

    +
    + +
    +

    + +

    +

    3. Most cited articles on Physics-informed GNNs

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    TitlePublicationDate#CitationsJournal/ConferencepublicationVenue
    Gradient-based learning applied to document recognitionNone46007Proc. IEEEProceedings of the IEEE
    Collective dynamics of ‘small-world’ networks1998-06-0438487NatureNature
    Semi-Supervised Classification with Graph Convolutional Networks2016-09-0922124ArXivInternational Conference on Learning Representations
    Statistical mechanics of complex networks2001-06-0618824ArXivarXiv.org
    The Structure and Function of Complex Networks2003-03-2516784SIAM Rev.SIAM Review
    TensorFlow: A system for large-scale machine learning2016-05-2716711{'pages': '265-283'}USENIX Symposium on Operating Systems Design and Implementation
    Community structure in social and biological networks2001-12-0714280Proceedings of the National Academy of Sciences of the United States of AmericaProceedings of the National Academy of Sciences of the United States of America
    Graph Attention Networks2017-10-3013990ArXivInternational Conference on Learning Representations
    PRISMA Extension for Scoping Reviews (PRISMA-ScR): Checklist and Explanation2018-10-0212793Annals of Internal MedicineAnnals of Internal Medicine
    Consensus problems in networks of agents with switching topology and time-delays2004-09-1311249IEEE Transactions on Automatic ControlIEEE Transactions on Automatic Control
    Authoritative sources in a hyperlinked environment1999-09-0110818{'pages': '668-677'}ACM-SIAM Symposium on Discrete Algorithms
    Complex brain networks: graph theoretical analysis of structural and functional systems2009-03-019834Nature Reviews NeuroscienceNature Reviews Neuroscience
    Consensus and Cooperation in Networked Multi-Agent Systems2007-03-059266Proceedings of the IEEEProceedings of the IEEE
    Gephi: An Open Source Software for Exploring and Manipulating Networks2009-03-198729Proceedings of the International AAAI Conference on Web and Social MediaInternational Conference on Web and Social Media
    DeepWalk: online learning of social representations2014-03-268216Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data miningKnowledge Discovery and Data Mining
    Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering2016-06-306409{'pages': '3837-3845'}Neural Information Processing Systems
    A Comprehensive Survey on Graph Neural NetworksNone5933IEEE Transactions on Neural Networks and Learning SystemsIEEE Transactions on Neural Networks and Learning Systems
    Neural Message Passing for Quantum Chemistry2017-04-045744{'pages': '1263-1272'}International Conference on Machine Learning
    The Graph Neural Network ModelNone5618IEEE Transactions on Neural NetworksIEEE Transactions on Neural Networks
    How Powerful are Graph Neural Networks?2018-10-015319ArXivInternational Conference on Learning Representations
    Factor graphs and the sum-product algorithm2001-02-015262IEEE Trans. Inf. TheoryIEEE Transactions on Information Theory
    Uncovering the overlapping community structure of complex networks in nature and society2005-06-095068NatureNature
    LINE: Large-scale Information Network Embedding2015-03-114739Proceedings of the 24th International Conference on World Wide WebThe Web Conference
    Tabu Search - Part INone4676INFORMS J. Comput.INFORMS journal on computing
    An automated method for finding molecular complexes in large protein interaction networks2003-01-134657BMC BioinformaticsBMC Bioinformatics
    Information flow and cooperative control of vehicle formations2004-09-134545IEEE Transactions on Automatic ControlIEEE Transactions on Automatic Control
    Finding community structure in networks using the eigenvectors of matrices.2006-05-104342Physical review. E, Statistical, nonlinear, and soft matter physicsNA
    Dynamic Graph CNN for Learning on Point Clouds2018-01-244327ACM Transactions on Graphics (TOG)ACM Transactions on Graphics
    The KEGG resource for deciphering the genomeNone4282Nucleic acids researchNA
    The PRISMA Extension Statement for Reporting of Systematic Reviews Incorporating Network Meta-analyses of Health Care Interventions: Checklist and Explanations2015-06-024250Annals of Internal MedicineAnnals of Internal Medicine
    Spectral Networks and Locally Connected Networks on Graphs2013-12-204224CoRRInternational Conference on Learning Representations
    Pregel: a system for large-scale graph processing2010-06-063877Proceedings of the 2010 ACM SIGMOD International Conference on Management of dataNA
    Graph Neural Networks: A Review of Methods and Applications2018-12-203733ArXivAI Open
    BioGRID: a general repository for interaction datasets2005-12-283714Nucleic Acids ResearchNA
    Modeling Relational Data with Graph Convolutional Networks2017-03-173647{'pages': '593-607'}Extended Semantic Web Conference
    Hierarchical Information Clustering by Means of Topologically Embedded Graphs2011-10-203629PLoS ONEPLoS ONE
    Using Bayesian networks to analyze expression data2000-04-083560{'pages': '127-135'}Annual International Conference on Research in Computational Molecular Biology
    The university of Florida sparse matrix collection2011-11-013524ACM Trans. Math. Softw.NA
    The architecture of complex weighted networks.2003-11-183521Proceedings of the National Academy of Sciences of the United States of AmericaProceedings of the National Academy of Sciences of the United States of America
    The emerging field of signal processing on graphs: Extending high-dimensional data analysis to networks and other irregular domains2012-10-313495IEEE Signal Processing MagazineIEEE Signal Processing Magazine
    Conn: A Functional Connectivity Toolbox for Correlated and Anticorrelated Brain Networks2012-08-063482Brain connectivityBrain Connectivity
    Random graphs with arbitrary degree distributions and their applications.2000-07-133408Physical review. E, Statistical, nonlinear, and soft matter physicsNA
    A Convolutional Neural Network for Modelling Sentences2014-04-083400{'pages': '655-665'}Annual Meeting of the Association for Computational Linguistics
    Measurement and analysis of online social networks2007-10-243252{'pages': '29-42'}ACM/SIGCOMM Internet Measurement Conference
    Small worlds: the dynamics of networks between order and randomness2000-11-013236SIGMOD Rec.NA
    BrainNet Viewer: A Network Visualization Tool for Human Brain Connectomics2013-07-043057PLoS ONEPLoS ONE
    Fibonacci heaps and their uses in improved network optimization algorithms1984-10-243036{'pages': '338-346'}NA
    The human disease network2007-05-223030Proceedings of the National Academy of SciencesProceedings of the National Academy of Sciences of the United States of America
    Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition2018-01-232989{'pages': '7444-7452'}AAAI Conference on Artificial Intelligence
    Convolutional Networks on Graphs for Learning Molecular Fingerprints2015-09-302989ArXivNeural Information Processing Systems
    +

    + +

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    4. Latest articles on Physics-informed GNNs

    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    TitlePublicationDate#CitationsJournal/ConferencepublicationVenue
    Hierarchical spatio-temporal graph convolutional neural networks for traffic data imputation2024-06-010Information FusionInformation Fusion
    Reagent dosage inference based on graph convolutional memory perception network for zinc roughing flotation2024-05-010Control Engineering PracticeControl Engineering Practice
    MACNS: A generic graph neural network integrated deep reinforcement learning based multi-agent collaborative navigation system for dynamic trajectory planning2024-05-010Inf. FusionInformation Fusion
    DawnGNN: Documentation augmented windows malware detection using graph neural network2024-05-010Computers & SecurityNA
    Multi-level Graph Memory Network Cluster Convolutional Recurrent Network for traffic forecasting2024-05-010Inf. FusionInformation Fusion
    FairCare: Adversarial training of a heterogeneous graph neural network with attention mechanism to learn fair representations of electronic health records2024-05-010Information Processing & ManagementNA
    Multi-criteria group decision making based on graph neural networks in Pythagorean fuzzy environment2024-05-011Expert Systems with ApplicationsExpert systems with applications
    POI recommendation for random groups based on cooperative graph neural networks2024-05-010Information Processing & ManagementNA
    Attention based multi-task interpretable graph convolutional network for Alzheimer’s disease analysis2024-04-010Pattern Recognition LettersPattern Recognition Letters
    A coarse-to-fine adaptive spatial–temporal graph convolution network with residuals for motor imagery decoding from the same limb2024-04-010Biomedical Signal Processing and ControlBiomedical Signal Processing and Control
    A new programmed method for retrofitting heat exchanger networks using graph machine learning2024-04-010Applied Thermal EngineeringApplied Thermal Engineering
    AAGNet: A graph neural network towards multi-task machining feature recognition2024-04-011Robotics Comput. Integr. Manuf.NA
    AKGNN-PC: An assembly knowledge graph neural network model with predictive value calibration module for refrigeration compressor performance prediction with assembly error propagation and data imbalance scenarios2024-04-010Advanced Engineering InformaticsAdvanced Engineering Informatics
    Vessel trajectory prediction based on spatio-temporal graph convolutional network for complex and crowded sea areas2024-04-010Ocean EngineeringOcean Engineering
    GCNGAT: Drug–disease association prediction based on graph convolution neural network and graph attention network2024-04-010Artificial Intelligence in MedicineArtificial Intelligence in Medicine
    KAGNN: Graph neural network with kernel alignment for heterogeneous graph learning2024-04-010Knowledge-Based SystemsKnowledge-Based Systems
    ASSL-HGAT: Active semi-supervised learning empowered heterogeneous graph attention network2024-04-010Knowledge-Based SystemsKnowledge-Based Systems
    Multi-hop graph pooling adversarial network for cross-domain remaining useful life prediction: A distributed federated learning perspective2024-04-011Reliability Engineering & System SafetyNA
    Agriculture crop yield prediction using inertia based cat swarm optimization2024-04-010International Journal of Electrical and Computer Engineering (IJECE)International Journal of Electrical and Computer Engineering (IJECE)
    Graph attention Network-Based model for multiple fault detection and identification of sensors in nuclear power plant2024-04-010Nuclear Engineering and DesignNuclear Engineering and Design
    A pruned-optimized weighted graph convolutional network for axial flow pump fault diagnosis with hydrophone signals2024-04-010Advanced Engineering InformaticsAdvanced Engineering Informatics
    Explainable train delay propagation: A graph attention network approach2024-04-010Transportation Research Part E: Logistics and Transportation ReviewNA
    Graph neural networks based framework to analyze social media platforms for malicious user detection2024-04-010Applied Soft ComputingApplied Soft Computing
    Digital twin modeling for stress prediction of single-crystal turbine blades based on graph convolutional network2024-04-010Journal of Manufacturing ProcessesJournal of Manufacturing Processes
    Design information-assisted graph neural network for modeling central air conditioning systems2024-04-010Advanced Engineering InformaticsAdvanced Engineering Informatics
    Unveiling community structures in static networks through graph variational Bayes with evolution information2024-04-010NeurocomputingNeurocomputing
    Control Laws for Partially Observable Min-Plus Systems Networks With Disturbances and Under Mutual Exclusion Constraints2024-04-010IEEE Robotics and Automation LettersIEEE Robotics and Automation Letters
    Multi-satellite cooperative scheduling method for large-scale tasks based on hybrid graph neural network and metaheuristic algorithm2024-04-010Advanced Engineering InformaticsAdvanced Engineering Informatics
    Identification of chronic obstructive pulmonary disease using graph convolutional network in electronic nose2024-04-010Indonesian Journal of Electrical Engineering and Computer ScienceIndonesian Journal of Electrical Engineering and Computer Science
    Network traffic prediction with Attention-based Spatial–Temporal Graph Network2024-04-010Computer NetworksComputer Networks
    Bearing fault detection by using graph autoencoder and ensemble learning.2024-03-030Scientific reportsScientific Reports
    Successful Implementation of the AIUM Standardized 4-Year Residency Ultrasound Curriculum in Obstetrics and Gynecology: Lessons Learned and Way Forward.2024-03-030Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in MedicineJournal of ultrasound in medicine
    Prediction of lncRNA and disease associations based on residual graph convolutional networks with attention mechanism.2024-03-020Scientific reportsScientific Reports
    Deep Attentional Implanted Graph Clustering Algorithm for the Visualization and Analysis of Social Networks2024-03-020Journal of Internet Services and Information SecurityJournal of Internet Services and Information Security
    Electrical facies of the Asmari Formation in the Mansouri oilfield, an application of multi-resolution graph-based and artificial neural network clustering methods.2024-03-020Scientific reportsScientific Reports
    Information-incorporated gene network construction with FDR control.2024-03-020BioinformaticsBioinformatics
    Attention-Based Learning for Predicting Drug-Drug Interactions in Knowledge Graph Embedding Based on Multisource Fusion Information2024-03-020International Journal of Intelligent SystemsInternational Journal of Intelligent Systems
    Walk in Views: Multi-view Path Aggregation Graph Network for 3D Shape Analysis2024-03-010Inf. FusionInformation Fusion
    Topic Modeling on Document Networks With Dirichlet Optimal Transport Barycenter2024-03-010IEEE Transactions on Knowledge and Data EngineeringIEEE Transactions on Knowledge and Data Engineering
    MCGCN: Multi-Correlation Graph Convolutional Network for Pedestrian Attribute Recognition2024-03-010IEICE Transactions on Information and SystemsNA
    Postdisaster Routing of Movable Energy Resources for Enhanced Distribution System Resilience: A Deep Reinforcement Learning-Based Approach2024-03-010IEEE Industry Applications MagazineIEEE Industry Applications Magazine
    Towards explaining graph neural networks via preserving prediction ranking and structural dependency2024-03-010Inf. Process. Manag.Information Processing & Management
    Who is Who on Ethereum? Account Labeling Using Heterophilic Graph Convolutional Network2024-03-012IEEE Transactions on Systems, Man, and Cybernetics: SystemsNA
    An EV Charging Station Load Prediction Method Considering Distribution Network Upgrade2024-03-010IEEE Transactions on Power SystemsIEEE Transactions on Power Systems
    Event-Based Bipartite Containment Control for Multi-Agent Networks Subject to Communication Delay2024-03-010IEEE Transactions on Network Science and EngineeringIEEE Transactions on Network Science and Engineering
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    Real-Time Joint Regulations of Frequency and Voltage for TSO-DSO Coordination: A Deep Reinforcement Learning-Based Approach2024-03-012IEEE Transactions on Smart GridIEEE Transactions on Smart Grid
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    +

    + + + + + \ No newline at end of file diff --git a/docs/Symbolic_regression.md b/docs/Symbolic_regression.md index c59856c4..3a380615 100644 --- a/docs/Symbolic_regression.md +++ b/docs/Symbolic_regression.md @@ -2,72 +2,258 @@ hide: - navigation --- - - - - - - - -### 1. Search query - - -*((symbolic regression) + dynamics)* - - - - -### 2. Symbolic regression articles and citations over time - - -![Symbolic regression](assets/Symbolic_regression.png) - - - - -### 3. Most cited articles on Symbolic regression - - - - -| Title | PublicationDate | #Citations | Journal/Conference | publicationVenue | -| --- | --- | --- | --- | --- | -| [Symbolic Dynamic Programming for First-Order MDPs](https://www.semanticscholar.org/paper/9d59f87b881017e6ef0198636a77ad04b7ebea7a) | 2001-08-04 | 277 | {'pages': '690-700'} | {'id': '67f7f831-711a-43c8-8785-1e09005359b5', 'name': 'International Joint Conference on Artificial Intelligence', 'type': 'conference', 'alternate\_names': ['Int Jt Conf Artif Intell', 'IJCAI'], 'url': 'http://www.ijcai.org/'} | -| [On Neural Differential Equations](https://www.semanticscholar.org/paper/1f7ba0832203ab808fc8d6706836c591754b79da) | 2022-02-04 | 124 | {'name': 'ArXiv', 'volume': 'abs/2202.02435'} | {'id': '1901e811-ee72-4b20-8f7e-de08cd395a10', 'name': 'arXiv.org', 'alternate\_names': ['ArXiv'], 'issn': '2331-8422', 'url': 'https://arxiv.org'} | -| [A Survey And Analysis Of Diversity Measures In Genetic Programming](https://www.semanticscholar.org/paper/a164d4e754c8ef81b9e56a3aefcfbe92a06af9b2) | 2002-07-09 | 104 | {'pages': '716-723'} | {'id': 'd732841e-83f9-49ec-95ca-389e5568634b', 'name': 'Annual Conference on Genetic and Evolutionary Computation', 'type': 'conference', 'alternate\_names': ['GECCO', 'Annu Conf Genet Evol Comput', 'Genet Evol Comput Conf', 'Genetic and Evolutionary Computation Conference'], 'url': 'http://www.sigevo.org/'} | -| [Prediction of dynamical systems by symbolic regression.](https://www.semanticscholar.org/paper/99c7d71317f3532cdcf83f072d644c236610221d) | 2016-02-15 | 91 | {'name': 'Physical review. E', 'pages': '\n 012214\n ', 'volume': '94 1-1'} | {'id': '19842b7b-a4d1-4f9a-9714-87d878cf6e73', 'name': 'Physical Review E', 'type': 'journal', 'alternate\_names': ['Phys rev E', 'Physical review. E', 'Phys Rev E'], 'issn': '1539-3755', 'alternate\_issns': ['1550-2376', '2470-0045'], 'url': 'https://journals.aps.org/pre/', 'alternate\_urls': ['http://pre.aps.org/', 'http://journals.aps.org/pre/']} | -| [Take Their Word for It: The Symbolic Role of Linguistic Style Matches in User Communities](https://www.semanticscholar.org/paper/7f701c60d0b73af3ad2b70c6303e0cac18fc47a4) | 2014-12-01 | 69 | {'name': 'MIS Q.', 'pages': '1201-1217', 'volume': '38'} | None | -| [Data Based Prediction of Blood Glucose Concentrations Using Evolutionary Methods](https://www.semanticscholar.org/paper/8c44933472c5f6e871197be88ba9477ac577ebc6) | 2017-08-08 | 67 | {'name': 'Journal of Medical Systems', 'pages': '1-20', 'volume': '41'} | {'id': '79c59592-820f-4ed1-87df-db795b4326be', 'name': 'Journal of medical systems', 'type': 'journal', 'alternate\_names': ['J Med Syst', 'Journal of Medical Systems', 'J med syst'], 'issn': '0148-5598', 'url': 'https://link.springer.com/journal/10916'} | -| [Who Is Responsible for the Gender Gap? The Dynamics of Men’s and Women’s Democratic Macropartisanship, 1950–2012](https://www.semanticscholar.org/paper/ea19352c48d8e1f514ed04c87262c6e2f2069616) | 2017-07-03 | 61 | {'name': 'Political Research Quarterly', 'pages': '749 - 761', 'volume': '70'} | None | -| [On the closed form computation of the dynamic matrices and their differentiations](https://www.semanticscholar.org/paper/ef2824bb7e720bc6448d7e8e4496a49f9a5d2717) | 2013-11-01 | 55 | {'name': '2013 IEEE/RSJ International Conference on Intelligent Robots and Systems', 'pages': '2364-2359'} | None | -| [Automatic rule identification for agent-based crowd models through gene expression programming](https://www.semanticscholar.org/paper/6e4abe45f2981c8e0dc0cc2e2615f7b1bb1fcd68) | 2014-05-05 | 49 | {'pages': '1125-1132'} | {'id': '6c3a9833-5fac-49d3-b7e7-64910bd40b4e', 'name': 'Adaptive Agents and Multi-Agent Systems', 'type': 'conference', 'alternate\_names': ['Adapt Agent Multi-agent Syst', 'International Joint Conference on Autonomous Agents & Multiagent Systems', 'Adapt Agent Multi-agents Syst', 'AAMAS', 'Adaptive Agents and Multi-Agents Systems', 'Int Jt Conf Auton Agent Multiagent Syst'], 'url': 'http://www.ifaamas.org/'} | -| [Rediscovering orbital mechanics with machine learning](https://www.semanticscholar.org/paper/0d774d92c9c03648a213e5dc416065b0b72d894e) | 2022-02-04 | 46 | {'name': 'Machine Learning: Science and Technology', 'volume': '4'} | None | - - - - - - -### 4. Latest articles on Symbolic regression - - - - -| Title | PublicationDate | #Citations | Journal/Conference | publicationVenue | -| --- | --- | --- | --- | --- | -| [Shared professional logics amongst managers and bureaucrats in Brazilian social security: a street-level mixed-methods study](https://www.semanticscholar.org/paper/3c2bc03831c40da210da5f02806386981973ba48) | 2024-02-20 | 0 | {'name': 'International Journal of Public Sector Management'} | {'id': '39bcb8aa-e2fe-4135-bdce-6794f52e3e76', 'name': 'International Journal of Public Sector Management', 'type': 'journal', 'alternate\_names': ['Int J Public Sect Manag'], 'issn': '0951-3558', 'url': 'https://www.emerald.com/insight/publication/issn/0951-3558', 'alternate\_urls': ['http://www.emeraldinsight.com/0951-3558.htm']} | -| [Excitation Trajectory Optimization for Dynamic Parameter Identification Using Virtual Constraints in Hands-on Robotic System](https://www.semanticscholar.org/paper/f5c21a0dd557e33b683cab99268d37b04cc912bd) | 2024-01-29 | 0 | {'name': 'ArXiv', 'volume': 'abs/2401.16566'} | {'id': '1901e811-ee72-4b20-8f7e-de08cd395a10', 'name': 'arXiv.org', 'alternate\_names': ['ArXiv'], 'issn': '2331-8422', 'url': 'https://arxiv.org'} | -| [Population Dynamics in Genetic Programming for Dynamic Symbolic Regression](https://www.semanticscholar.org/paper/0fa5509ee2975b72c8a47ba5f0a60b84774cfd80) | 2024-01-10 | 0 | {'name': 'Applied Sciences'} | {'id': '136edf8d-0f88-4c2c-830f-461c6a9b842e', 'name': 'Applied Sciences', 'type': 'journal', 'alternate\_names': ['Appl Sci'], 'issn': '2076-3417', 'url': 'http://www.e-helvetica.nb.admin.ch/directAccess?callnumber=bel-217814', 'alternate\_urls': ['http://www.mathem.pub.ro/apps/', 'https://www.mdpi.com/journal/applsci', 'http://nbn-resolving.de/urn/resolver.pl?urn=urn:nbn:ch:bel-217814']} | -| [Reassessing the transport properties of fluids: A symbolic regression approach.](https://www.semanticscholar.org/paper/7864dd40fc44eb8517ef0e87b7f9e965772ece9d) | 2024-01-01 | 0 | {'name': 'Physical review. E', 'pages': '\n 015105\n ', 'volume': '109 1-2'} | {'id': '19842b7b-a4d1-4f9a-9714-87d878cf6e73', 'name': 'Physical Review E', 'type': 'journal', 'alternate\_names': ['Phys rev E', 'Physical review. E', 'Phys Rev E'], 'issn': '1539-3755', 'alternate\_issns': ['1550-2376', '2470-0045'], 'url': 'https://journals.aps.org/pre/', 'alternate\_urls': ['http://pre.aps.org/', 'http://journals.aps.org/pre/']} | -| [(Invited) Electrochemical Interfaces in Energy Storage: Theory Meets Experiment](https://www.semanticscholar.org/paper/d97335e9ed5301ea056f8957faa5f5b7ef105fac) | 2023-12-22 | 0 | {'name': 'ECS Meeting Abstracts'} | {'id': '4718308a-312e-40e7-a6f2-5110d1359b6a', 'name': 'ECS Meeting Abstracts', 'alternate\_names': ['EC Meet Abstr'], 'issn': '1091-8213', 'url': 'http://ma.ecsdl.org/'} | -| [AI-Lorenz: A physics-data-driven framework for black-box and gray-box identification of chaotic systems with symbolic regression](https://www.semanticscholar.org/paper/f5cccd316e70bd2366e67260e1f691761bd512d3) | 2023-12-21 | 0 | {'name': 'ArXiv', 'volume': 'abs/2312.14237'} | {'id': '1901e811-ee72-4b20-8f7e-de08cd395a10', 'name': 'arXiv.org', 'alternate\_names': ['ArXiv'], 'issn': '2331-8422', 'url': 'https://arxiv.org'} | -| [Machine Learning-Based Approach to Wind Turbine Wake Prediction under Yawed Conditions](https://www.semanticscholar.org/paper/ef9533aa3205d0fc999fa12e703d43899f09191b) | 2023-11-04 | 2 | {'name': 'Journal of Marine Science and Engineering'} | {'id': 'fff3549c-df24-4aef-accb-a33ae442a828', 'name': 'Journal of Marine Science and Engineering', 'type': 'journal', 'alternate\_names': ['J Mar Sci Eng'], 'issn': '2077-1312', 'url': 'https://www.mdpi.com/journal/jmse'} | -| [Boolformer: Symbolic Regression of Logic Functions with Transformers](https://www.semanticscholar.org/paper/ca6fb9d804aa339c0ba686545ddb78d4c5e45e02) | 2023-09-21 | 1 | {'name': 'ArXiv', 'volume': 'abs/2309.12207'} | {'id': '1901e811-ee72-4b20-8f7e-de08cd395a10', 'name': 'arXiv.org', 'alternate\_names': ['ArXiv'], 'issn': '2331-8422', 'url': 'https://arxiv.org'} | -| [GPSINDy: Data-Driven Discovery of Equations of Motion](https://www.semanticscholar.org/paper/7aa4950045a9a790857d169f999a479da147a3f3) | 2023-09-20 | 0 | {'name': 'ArXiv', 'volume': 'abs/2309.11076'} | {'id': '1901e811-ee72-4b20-8f7e-de08cd395a10', 'name': 'arXiv.org', 'alternate\_names': ['ArXiv'], 'issn': '2331-8422', 'url': 'https://arxiv.org'} | -| [Symbolic regression via neural networks.](https://www.semanticscholar.org/paper/eddffa1f2cf18c7ca4edbdaf01fd805f415aa4b8) | 2023-08-01 | 2 | {'name': 'Chaos', 'volume': '33 8'} | {'id': '30c0ded7-c8b4-473c-bbc0-f237234ac1a6', 'name': 'Chaos', 'type': 'journal', 'issn': '1054-1500', 'url': 'http://chaos.aip.org/', 'alternate\_urls': ['https://aip.scitation.org/journal/cha']} | - - - - - - + + + + + + + + +

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    Table of Contents

    +
  • 1. Search Query
    • +
  • 2. Symbolic regression articles and citations over time
    • +
  • 3. Most cited articles on Symbolic regression
    • +
  • 4. Latest articles on Symbolic regression
    • +

    + +

    +

    1. Search query

    + ((symbolic regression) + dynamics) +

    + +

    +

    2. Symbolic regression articles and citations over time

    +
    + +
    +

    + +

    +

    3. Most cited articles on Symbolic regression

    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    TitlePublicationDate#CitationsJournal/ConferencepublicationVenue
    Symbolic Dynamic Programming for First-Order MDPs2001-08-04277{'pages': '690-700'}International Joint Conference on Artificial Intelligence
    On Neural Differential Equations2022-02-04124ArXivarXiv.org
    A Survey And Analysis Of Diversity Measures In Genetic Programming2002-07-09104{'pages': '716-723'}Annual Conference on Genetic and Evolutionary Computation
    Prediction of dynamical systems by symbolic regression.2016-02-1591Physical review. EPhysical Review E
    Take Their Word for It: The Symbolic Role of Linguistic Style Matches in User Communities2014-12-0169MIS Q.NA
    Data Based Prediction of Blood Glucose Concentrations Using Evolutionary Methods2017-08-0867Journal of Medical SystemsJournal of medical systems
    Who Is Responsible for the Gender Gap? The Dynamics of Men’s and Women’s Democratic Macropartisanship, 1950–20122017-07-0361Political Research QuarterlyNA
    On the closed form computation of the dynamic matrices and their differentiations2013-11-01552013 IEEE/RSJ International Conference on Intelligent Robots and SystemsNA
    Automatic rule identification for agent-based crowd models through gene expression programming2014-05-0549{'pages': '1125-1132'}Adaptive Agents and Multi-Agent Systems
    Rediscovering orbital mechanics with machine learning2022-02-0446Machine Learning: Science and TechnologyNA
    +

    + +

    +

    4. Latest articles on Symbolic regression

    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    TitlePublicationDate#CitationsJournal/ConferencepublicationVenue
    Shared professional logics amongst managers and bureaucrats in Brazilian social security: a street-level mixed-methods study2024-02-200International Journal of Public Sector ManagementInternational Journal of Public Sector Management
    Excitation Trajectory Optimization for Dynamic Parameter Identification Using Virtual Constraints in Hands-on Robotic System2024-01-290ArXivarXiv.org
    Population Dynamics in Genetic Programming for Dynamic Symbolic Regression2024-01-100Applied SciencesApplied Sciences
    Reassessing the transport properties of fluids: A symbolic regression approach.2024-01-010Physical review. EPhysical Review E
    (Invited) Electrochemical Interfaces in Energy Storage: Theory Meets Experiment2023-12-220ECS Meeting AbstractsECS Meeting Abstracts
    AI-Lorenz: A physics-data-driven framework for black-box and gray-box identification of chaotic systems with symbolic regression2023-12-210ArXivarXiv.org
    Machine Learning-Based Approach to Wind Turbine Wake Prediction under Yawed Conditions2023-11-042Journal of Marine Science and EngineeringJournal of Marine Science and Engineering
    Boolformer: Symbolic Regression of Logic Functions with Transformers2023-09-211ArXivarXiv.org
    GPSINDy: Data-Driven Discovery of Equations of Motion2023-09-200ArXivarXiv.org
    Symbolic regression via neural networks.2023-08-012ChaosChaos
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    +

    Table of Contents

    +
  • 1. Search Query
    • +
  • 2. {{title}} articles and citations over time
    • +
  • 3. Most cited articles on {{title}}
    • +
  • 4. Latest articles on {{title}}
    • +

    +

    -

    1. Search query

    +

    1. Search query

    {{query}}

    -

    2. {{title}} articles and citations over time

    - {{title}} +

    2. {{title}} articles and citations over time

    +
    + +

    -

    3. Most cited articles on {{title}}

    - +

    3. Most cited articles on {{title}}

    +
    @@ -30,7 +41,7 @@ {% for article in most_cited_articles %} - + @@ -42,25 +53,59 @@

    -

    4. Latest articles on {{title}}

    -
    Title
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a/templates/category.txt +++ b/templates/category.txt @@ -5,19 +5,30 @@ + +