Add README (#3)

* fix: change time label to UTC (#1)

* fix: Add README (#2)

* fix: publication column on overview-page; inc. num articles to 100 (#4)

* Update README.md (#5)

Correct a typo in readme.

* Feat update query and improve page style (#6)

* chore: add query terms to PINNS

* chore: add query terms to PINNS

* chore: change order of terms

* chore: add query terms to neural ODEs

* chore: further query terms

* feat: add css file to main.html

* feat: add css file to main.html

* feat: edit font color

* feat: remove the path to custom.css file

---------

Co-authored-by: lilijap <43205236+lilijap@users.noreply.github.com>

README.md

@@ -5,7 +5,54 @@
 
 <h1 align="center" style="border-bottom: none;">🚀 Literature Survey</h1>
 
-This repository serves as a template to develop a repo on literature survey.
-View the documentation of the example code used in the repo @ https://virtualpatientengine.github.io/literatureSurvey
+Welcome to the Literature Survey Template Repository! 📚✨ This repository provides you with a nifty setup to create your very own automated literature survey repository. Say goodbye to manual searching and hello to automated updates every Monday morning at 6 am UTC!
 
->NOTE: Read more about these and other features in the CodeOps and DevOps documents available on the teams channel.
+### But Wait, There's More!
+Not only does this repo automatically fetch the most cited and latest articles in your field, but it also presents them to you in pretty web pages with interactive tables and plots!
+
+### Example Usage
+For demonstration purposes, this template repository uses the keywords related to the simulator module of Team VPE as an example. You can easily customize it to your own fields of interest by following the steps outlined below. To see how the automated literature survey repo looks like, visit this [link](https://virtualpatientengine.github.io/literatureSurvey).
+
+Let's dive in and set up your own literature survey adventure!
+
+### Getting Started
+Follow these simple steps to set up your literature survey repository:
+
+1. Click on the ```Use this template``` button to create your own repository based on this template.
+
+2. Open up the ```app/data/query.tsv``` file in your favorite code editor or Excel.
+
+3. Get creative! Under the title columns, give catchy titles to your sections and under the Query column, define their correspondng queries. Need help? Check out Semantic Scholar's query [parameter definition](https://api.semanticscholar.org/api-docs/#tag/Paper-Data/operation/get_graph_paper_bulk_search).
+
+4. Let's create a venv:
+```
+> python -m venv env
+# On Windows
+> .\env\Scripts\activate
+
+# On macOS and Linux
+> source env/bin/activate
+```
+
+5. Install all the necessary requirements:
+```
+> pip3 install -r requirements.txt
+```
+
+6. It's time to fetch some literature! Run the ```literature_fetch.py``` script to grab those juicy papers from Semantic Scholar:
+```
+> cd app/code
+> python3 literature_fetch.py
+```
+
+7. Now, fire up MkDocs to see how your survey is shaping up locally:
+```
+> mkdocs serve
+```
+
+Head over to the localhost link that pops up in your terminal. Marvel at the beauty of your survey pages. Once you're satisfied, commit your code and open up a PR. If you have any questions or need assistance, feel free to reach out to the Team VPE Code/DevOps guides or contact Gurdeep.
+
+### Bugs? Feature Requests? I've Got You Covered
+If you encounter any bugs or have brilliant ideas for new features, don't hesitate to head over to the "Issues" tab and let me know.
+
+### Happy surveying! 📖🔍

app/code/literature_fetch.py

@@ -24,7 +24,7 @@
     # 'sort': 'citationCount:desc',
     'token': None
 }
-N = 7
+N = 100
 DIC = {}
 
 def fetch_articles(search_query,

app/data/query.tsv

@@ -1,7 +1,7 @@
 Title	Query
-Neural ODEs	(neural ordinary differential equation) | (neural ODE) | (graph neural differential equation) | (graph neural diffusion) | (graph neural ODEs)
-Physics-informed GNNs	(graph networks) | (physics constrain) | (learned simulator) | (learned simulation)
 Symbolic regression	((symbolic regression) + dynamics)
-PINNs	(physics-informed neural computing)
+PINNs	("physics-informed neural computing") | ("physics-informed neural networks") | ("physics-informed deep learning")
 Latent Space Simulator	(VAMP) | (latent space simul*) | (decomposition of koopman operator) | (time-lagged autoencoder)
 Koopman Theory	(koopman*) | (transformations in hilbert space) | (linear transformation of PDEs) | (regularization of physics-informed machine learning)
+Neural ODEs	(neural ordinary differential equation) | (neural ODE) | (graph neural differential equation) | (graph neural diffusion) | (graph neural ODEs) | (neural ODE solvers)
+Physics-informed GNNs	((graph networks) + (physics constrain*)) | ("learned simulator"~1) | ("learned simulation"~1)

base.yml

@@ -28,8 +28,8 @@ theme:
         name: Switch to light mode    
       primary: red
       accent: lime
-# extra_css:
-#   - custom.css
+extra_css:
+  - custom.css
 # use_directory_urls: false
 
 repo_url: https://github.com/VirtualPatientEngine/literatureSurvey