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Koopman Theory

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3. Most cited articles on Koopman Theory

Hamiltonian Systems and Transformation in Hilbert Space. B. O. Koopman 1931-05-01 Proceedings of the National Academy of Sciences of the United States of America - 1585 + 1589 A Data–Driven Approximation of the Koopman Operator: Extending Dynamic Mode Decomposition Matthew O. Williams, I. Kevrekidis, C. Rowley 2014-08-19 Journal of Nonlinear Science - 1345 + 1350 Deep learning for universal linear embeddings of nonlinear dynamics Bethany Lusch, J. Kutz, S. Brunton 2017-12-27 Nature Communications - 924 + 925 Entanglement renormalization. G. Vidal 2005-12-08 Physical review letters - 787 + 788 @@ -688,112 +688,112 @@

3. Most cited articles on Koopman Theory

CT Imaging of the 2019 Novel Coronavirus (2019-nCoV) Pneumonia J. Lei, Junfeng Li, Xun Li, X. Qi 2020-01-31 Radiology - 659 + 658 Linear predictors for nonlinear dynamical systems: Koopman operator meets model predictive control Milan Korda, I. Mezić 2016-11-10 Autom. - 650 + 651 Variants of Dynamic Mode Decomposition: Boundary Condition, Koopman, and Fourier Analyses Kevin K. Chen, Jonathan H. Tu, C. Rowley 2012-04-27 Journal of Nonlinear Science - 646 + 648 Algorithms for the Split Variational Inequality Problem Y. Censor, A. Gibali, S. Reich 2010-09-20 Numerical Algorithms - 599 + 600 Quantum singular value transformation and beyond: exponential improvements for quantum matrix arithmetics A. Gilyén, Yuan Su, G. Low, N. Wiebe 2018-06-05 Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing - 489 + 493 Surface Matching via Currents M. Vaillant, J. Glaunès 2005-07-10 Information processing in medical imaging : proceedings of the ... conference - 454 + 455 Koopman Invariant Subspaces and Finite Linear Representations of Nonlinear Dynamical Systems for Control S. Brunton, Bingni W. Brunton, J. Proctor, J. Kutz 2015-10-11 PLoS ONE - 438 + 439 Robust Feature Matching for Remote Sensing Image Registration via Locally Linear Transforming Jiayi Ma, Huabing Zhou, Ji Zhao, Yuan Gao, Junjun Jiang, J. Tian 2015-06-19 IEEE Transactions on Geoscience and Remote Sensing - 422 + 421 Adiabatic density-functional perturbation theory. X. Gonze 1995-08-01 Physical review. A, Atomic, molecular, and optical physics - 419 + 420 Chaos as an intermittently forced linear system S. Brunton, Bingni W. Brunton, J. Proctor, E. Kaiser, J. Kutz 2016-08-18 Nature Communications - 417 + 419 @@ -820,45 +820,45 @@

3. Most cited articles on Koopman Theory

On Koopmans' theorem in density functional theory. T. Tsuneda, Jong-Won Song, Satoshi Suzuki, K. Hirao 2010-11-01 The Journal of chemical physics - 356 + 359 Characterizing possible failure modes in physics-informed neural networks A. Krishnapriyan, A. Gholami, Shandian Zhe, Robert M. Kirby, Michael W. Mahoney 2021-09-02 Neural Information Processing Systems - 348 + 351 - Proof of the Quasi-Ergodic Hypothesis. - J. Neumann - None - Proceedings of the National Academy of Sciences of the United States of America - 339 + Ergodic Theory, Dynamic Mode Decomposition, and Computation of Spectral Properties of the Koopman Operator + Hassan Arbabi, I. Mezić + 2016-11-21 + SIAM J. Appl. Dyn. Syst. + 340 - Ergodic Theory, Dynamic Mode Decomposition, and Computation of Spectral Properties of the Koopman Operator - Hassan Arbabi, I. Mezić - 2016-11-21 - SIAM J. Appl. Dyn. Syst. + Proof of the Quasi-Ergodic Hypothesis. + J. Neumann + None + Proceedings of the National Academy of Sciences of the United States of America 339 @@ -897,13 +897,13 @@

3. Most cited articles on Koopman Theory

Extended dynamic mode decomposition with dictionary learning: A data-driven adaptive spectral decomposition of the Koopman operator. Qianxiao Li, Felix Dietrich, E. Bollt, I. Kevrekidis 2017-07-02 Chaos - 323 + 324 @@ -919,13 +919,13 @@

3. Most cited articles on Koopman Theory

Fundamental gaps in finite systems from eigenvalues of a generalized Kohn-Sham method. T. Stein, Helen R. Eisenberg, L. Kronik, R. Baer 2010-06-28 Physical review letters - 315 + 316 @@ -941,57 +941,57 @@

3. Most cited articles on Koopman Theory

Learning Deep Neural Network Representations for Koopman Operators of Nonlinear Dynamical Systems Enoch Yeung, Soumya Kundu, Nathan Oken Hodas 2017-08-22 2019 American Control Conference (ACC) - 306 + 311 - Non-Rigid Point Set Registration by Preserving Global and Local Structures - Jiayi Ma, Ji Zhao, A. Yuille - None - IEEE Transactions on Image Processing + Experimental realization of universal geometric quantum gates with solid-state spins + C. Zu, Wenhe Wang, L. He, Wenhao Zhang, Chengyu Dai, Feida Wang, Luming Duan + 2014-10-01 + Nature 298 - Experimental realization of universal geometric quantum gates with solid-state spins - C. Zu, Wenhe Wang, L. He, Wenhao Zhang, Chengyu Dai, Feida Wang, Luming Duan - 2014-10-01 - Nature - 298 + Non-Rigid Point Set Registration by Preserving Global and Local Structures + Jiayi Ma, Ji Zhao, A. Yuille + None + IEEE Transactions on Image Processing + 297 A Kernel Between Sets of Vectors R. Kondor, Tony Jebara 2003-08-21 International Conference on Machine Learning - 294 + 295 On Convergence of Extended Dynamic Mode Decomposition to the Koopman Operator Milan Korda, I. Mezić 2017-03-14 Journal of Nonlinear Science - 292 + 293 @@ -1018,24 +1018,24 @@

3. Most cited articles on Koopman Theory

- Data-driven discovery of Koopman eigenfunctions for control - E. Kaiser, J. Kutz, S. Brunton - 2017-07-04 - Machine Learning: Science and Technology - 257 + Understanding and mitigating gradient pathologies in physics-informed neural networks + Sifan Wang, Yujun Teng, P. Perdikaris + 2020-01-13 + ArXiv + 259 - Understanding and mitigating gradient pathologies in physics-informed neural networks - Sifan Wang, Yujun Teng, P. Perdikaris - 2020-01-13 - ArXiv - 257 + Data-driven discovery of Koopman eigenfunctions for control + E. Kaiser, J. Kutz, S. Brunton + 2017-07-04 + Machine Learning: Science and Technology + 258 @@ -1051,13 +1051,13 @@

3. Most cited articles on Koopman Theory

Quantum computing by an optimal control algorithm for unitary transformations. J. P. Palao, R. Kosloff 2002-04-18 Physical review letters - 252 + 253 @@ -1073,13 +1073,13 @@

3. Most cited articles on Koopman Theory

Modern Koopman Theory for Dynamical Systems S. Brunton, M. Budišić, E. Kaiser, J. Kutz 2021-02-24 SIAM Rev. - 238 + 239 @@ -1139,35 +1139,35 @@

3. Most cited articles on Koopman Theory

- LSDT: Latent Sparse Domain Transfer Learning for Visual Adaptation - Lei Zhang, W. Zuo, D. Zhang - 2016-01-12 - IEEE Transactions on Image Processing - 208 + One Health: A new definition for a sustainable and healthy future + W. Adisasmito, Salama Almuhairi, C. B. Behravesh, Pépé Bilivogui, S. Bukachi, N. Casas, Natalia Margarita Cediel Becerra, D. Charron, A. Chaudhary, Janice R. Ciacci Zanella, A. Cunningham, Osman Dar, Nitish Debnath, Baptiste Dungu, E. Farag, George F. Gao, D. Hayman, M. Khaitsa, M. Koopmans, C. Machalaba, J. Mackenzie, W. Markotter, T. Mettenleiter, Serge Morand, V. Smolenskiy, Lei Zhou + 2022-06-01 + PLoS Pathogens + 209 - One Health: A new definition for a sustainable and healthy future - W. Adisasmito, Salama Almuhairi, C. B. Behravesh, Pépé Bilivogui, S. Bukachi, N. Casas, Natalia Margarita Cediel Becerra, D. Charron, A. Chaudhary, Janice R. Ciacci Zanella, A. Cunningham, Osman Dar, Nitish Debnath, Baptiste Dungu, E. Farag, George F. Gao, D. Hayman, M. Khaitsa, M. Koopmans, C. Machalaba, J. Mackenzie, W. Markotter, T. Mettenleiter, Serge Morand, V. Smolenskiy, Lei Zhou - 2022-06-01 - PLoS Pathogens - 206 + LSDT: Latent Sparse Domain Transfer Learning for Visual Adaptation + Lei Zhang, W. Zuo, D. Zhang + 2016-01-12 + IEEE Transactions on Image Processing + 209 Variational Approach for Learning Markov Processes from Time Series Data Hao Wu, Frank No'e 2017-07-14 Journal of Nonlinear Science - 197 + 199 @@ -1293,13 +1293,13 @@

3. Most cited articles on Koopman Theory

A rise in plasma creatinine that is not a sign of renal failure: which drugs can be responsible? E. Andreev, M. Koopman, L. Arisz 1999-09-01 Journal of Internal Medicine - 162 + 163 @@ -1315,24 +1315,24 @@

3. Most cited articles on Koopman Theory

Koopman operator-based model reduction for switched-system control of PDEs Sebastian Peitz, Stefan Klus 2017-10-18 Autom. - 153 + 154 Robust L2E Estimation of Transformation for Non-Rigid Registration Jiayi Ma, Weichao Qiu, Ji Zhao, Yong Ma, A. Yuille, Z. Tu None IEEE Trans. Signal Process. - 140 + 144 @@ -1491,24 +1491,24 @@

3. Most cited articles on Koopman Theory

Variational Koopman models: Slow collective variables and molecular kinetics from short off-equilibrium simulations. Hao Wu, F. Nüske, Fabian Paul, Stefan Klus, P. Koltai, F. Noé 2016-10-20 The Journal of chemical physics - 105 + 106 Infinite Dimensional Backstepping-Style Feedback Transformations for a Heat Equation with an Arbitrary Level of Instability A. Balogh, M. Krstić None Eur. J. Control - 103 + 104 @@ -1612,23 +1612,23 @@

3. Most cited articles on Koopman Theory

- A hospital facility layout problem finally solved - P. Hahn, J. Krarup - 2001-10-01 - Journal of Intelligent Manufacturing - 94 + Estimation of electron transfer parameters from AM1 calculations. + and Stephen F. Nelsen, Fredrik Blomgren + 2001-08-30 + The Journal of organic chemistry + 95 - Estimation of electron transfer parameters from AM1 calculations. - and Stephen F. Nelsen, Fredrik Blomgren - 2001-08-30 - The Journal of organic chemistry + A hospital facility layout problem finally solved + P. Hahn, J. Krarup + 2001-10-01 + Journal of Intelligent Manufacturing 94 @@ -1689,34 +1689,23 @@

3. Most cited articles on Koopman Theory

- General Method for Solving the Split Common Fixed Point Problem - A. Cegielski - 2015-05-01 - Journal of Optimization Theory and Applications - 90 - - - - Self-consistent solution of the Dyson equation for atoms and molecules within a conserving approximation. N. Dahlen, Robert van Leeuwen 2005-04-22 The Journal of chemical physics - 90 + 91 - Antagonistic regulation of Cyp26b1 by transcription factors SOX9/SF1 and FOXL2 during gonadal development in mice - K. Kashimada, T. Svingen, C. Feng, E. Pelosi, Stefan Bagheri-Fam, V. Harley, D. Schlessinger, J. Bowles, P. Koopman - 2011-07-14 - The FASEB Journal + General Method for Solving the Split Common Fixed Point Problem + A. Cegielski + 2015-05-01 + Journal of Optimization Theory and Applications 90 @@ -1731,6 +1720,17 @@

3. Most cited articles on Koopman Theory

90 + + + Antagonistic regulation of Cyp26b1 by transcription factors SOX9/SF1 and FOXL2 during gonadal development in mice + K. Kashimada, T. Svingen, C. Feng, E. Pelosi, Stefan Bagheri-Fam, V. Harley, D. Schlessinger, J. Bowles, P. Koopman + 2011-07-14 + The FASEB Journal + 89 + +

@@ -1757,6 +1757,30 @@

4. Latest articles on Koopman Theory

0 + + Impact of Newtonian heating on MHD flow of non-Newtonian fluid + H. Alqahtani + 2024-04-03 + International Journal of Modern Physics B + 0 + + + + Skypen met een koopman des doods + Yarin Eski + 2024-04-01 + Tijdschrift over Cultuur & Criminaliteit + 0 + + + + Recueil des sotties françaises, ii. Édité par Marie Bouhaïk-Gironès, Jelle Koopmans et Katell Lavéant. Sous la direction de Jelle Koopmans + Sarah Gordon + 2024-04-01 + French Studies + 0 + + Semantic and Logical Communication-Control Codesign for Correlated Dynamical Systems Abanoub M. Girgis, Hyowoon Seo, Jihong Park, M. Bennis @@ -1861,6 +1885,14 @@

4. Latest articles on Koopman Theory

0 + + Mixed Algorithm of SINDy and HAVOK for Measure-Based Analysis of Power System with Inverter-based Resource + R. S. Kandezy, J. Jiang + 2024-03-14 + International Journal of Innovative Science and Research Technology (IJISRT) + 0 + + Beyond trade statistics: how much do exports actually contribute to domestic value added? Maria Llop @@ -1877,6 +1909,22 @@

4. Latest articles on Koopman Theory

0 + + Koopman Ensembles for Probabilistic Time Series Forecasting + Anthony Frion, Lucas Drumetz, G. Tochon, M. Mura, Albdeldjalil Aissa El Bey + 2024-03-11 + ArXiv + 0 + + + + C3D: Cascade Control with Change Point Detection and Deep Koopman Learning for Autonomous Surface Vehicles + Jianwen Li, Hyunsang Park, Wenjian Hao, Lei Xin, Jalil Chavez-Galaviz, Ajinkya Chaudhary, Meredith Bloss, Kyle Pattison, Christopher Vo, Devesh Upadhyay, Shreyas Sundaram, Shaoshuai Mou, N. Mahmoudian + 2024-03-09 + ArXiv + 0 + + Model-Based Linear Control of Nonlinear Pneumatic Soft Bending Actuators Jiajin Wang, Baoguo Xu, Jian-yang Lai, Xin Wang, Ye Lu, Cong Hu, Huijun Li, Aiguo Song @@ -1885,6 +1933,22 @@

4. Latest articles on Koopman Theory

0 + + Dynamic Gaussian Graph Operator: Learning parametric partial differential equations in arbitrary discrete mechanics problems + Chu Wang, Jinhong Wu, Yanzhi Wang, Zhijian Zha, Qi Zhou + 2024-03-05 + ArXiv + 0 + + + + Koopman-Assisted Reinforcement Learning + Preston Rozwood, Edward Mehrez, Ludger Paehler, Wen Sun, S. Brunton + 2024-03-04 + ArXiv + 2 + + A Data-Driven Koopman Approach for Power System Nonlinear Dynamic Observability Analysis Yijun Xu, Qinling Wang, L. Mili, Zongsheng Zheng, W. Gu, Shuai Lu, Zhi Wu @@ -2178,7 +2242,7 @@

4. Latest articles on Koopman Theory

Liang Wu, Krystian Ganko, Richard D. Braatz 2024-01-09 ArXiv - 2 + 3 @@ -2258,7 +2322,7 @@

4. Latest articles on Koopman Theory

M. Abbas, Nargis Khan, M. S. Hashmi, Mostafa Inc 2023-12-30 Modern Physics Letters B - 1 + 2 @@ -2279,7 +2343,7 @@

4. Latest articles on Koopman Theory

Estimation and Prediction of the Polymers’ Physical Characteristics Using the Machine Learning Models - I. Malashin, V. Tynchenko, V. A. Nelyub, Aleksei Borodulin, Andrei P. Gantimurov + Ivan Malashin, V. Tynchenko, V. A. Nelyub, Aleksei Borodulin, Andrei P. Gantimurov 2023-12-29 Polymers 2 @@ -2485,70 +2549,6 @@

4. Latest articles on Koopman Theory

0 - - Fusion of Ultrasound and Magnetic Resonance Images for Endometriosis Diagnosis: A Non-Parametric Approach - Youssra El Bennioui, Alexandre Bruguier, Fabien Vidal, Adrian Basarab, J. Tourneret - 2023-12-10 - 2023 IEEE 9th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP) - 0 - - - - Enhancing interpretability and generalizability of deep learning-based emulator in three-dimensional lake hydrodynamics using Koopman operator and transfer learning: Demonstrated on the example of lake Zurich. - Wenchong Tian, Zhiyu Zhang, D. Bouffard, Hao Wu, K. Xin, Xianyong Gu, Z. Liao - 2023-12-10 - Water research - 0 - - - - Utrecht bouwt 1945-1975 | Post 65 - Een turbulente tijd | Experimentele woningbouw in Nederland 1968-1980 - Marie-Thérèse Van Thoor - 2023-12-09 - Bulletin KNOB - 0 - - - - Trajectory Estimation in Unknown Nonlinear Manifold Using Koopman Operator Theory - Yanran Wang, Michael J. Banks, Igor Mezic, Takashi Hikihara - 2023-12-09 - ArXiv - 0 - - - - Deep Learning for Koopman-based Dynamic Movement Primitives - Tyler Han, Carl Glen Henshaw - 2023-12-06 - ArXiv - 0 - - - - Koopman model predictive control based load modulation for primary frequency regulation - A. Husham, Innocent Kamwa, Hussein Suprême - 2023-12-06 - IET Generation, Transmission & Distribution - 0 - - - - Dynamic mode decomposition for Koopman spectral analysis of elementary cellular automata. - Keisuke Taga, Yuzuru Kato, Yoshihiro Yamazaki, Y. Kawahara, H. Nakao - 2023-12-04 - Chaos - 0 - - - - KEEC: Embed to Control on An Equivariant Geometry - Xiaoyuan Cheng, Yiming Yang, Wei Jiang, Yukun Hu - 2023-12-04 - ArXiv - 0 - -

@@ -2558,14 +2558,14 @@

4. Latest articles on Koopman Theory

Denoising Diffusion Implicit Models Jiaming Song, Chenlin Meng, Stefano Ermon 2020-10-06 ArXiv - 2824 + 2889 @@ -655,46 +655,46 @@

3. Most cited articles on Latent Space Simulator A Data–Driven Approximation of the Koopman Operator: Extending Dynamic Mode Decomposition Matthew O. Williams, I. Kevrekidis, C. Rowley 2014-08-19 Journal of Nonlinear Science - 1345 + 1350 Deep Autoencoding Gaussian Mixture Model for Unsupervised Anomaly Detection Bo Zong, Qi Song, Martin Renqiang Min, Wei Cheng, C. Lumezanu, Dae-ki Cho, Haifeng Chen 2018-02-15 - 1260 + 1268 Botulinum neurotoxin A selectively cleaves the synaptic protein SNAP-25 J. Blasi, E. Chapman, E. Link, T. Binz, S. Yamasaki, P. Camilli, T. Südhof, H. Niemann, R. Jahn 1993-09-09 Nature - 1165 + 1167 Poincaré Embeddings for Learning Hierarchical Representations Maximilian Nickel, Douwe Kiela 2017-05-22 ArXiv - 1045 + 1052 @@ -710,13 +710,13 @@

3. Most cited articles on Latent Space Simulator Cross-domain sentiment classification via spectral feature alignment Sinno Jialin Pan, Xiaochuan Ni, Jian-Tao Sun, Qiang Yang, Zheng Chen 2010-04-26 The Web Conference - 795 + 794 @@ -732,35 +732,35 @@

3. Most cited articles on Latent Space Simulator Towards K-means-friendly Spaces: Simultaneous Deep Learning and Clustering Bo Yang, Xiao Fu, N. Sidiropoulos, Mingyi Hong 2016-10-15 International Conference on Machine Learning - 740 + 744 VBF: Vector-Based Forwarding Protocol for Underwater Sensor Networks Peng Xie, Jun-hong Cui, Li Lao 2006-05-15 NotAvbl - 734 + 735 HAQ: Hardware-Aware Automated Quantization With Mixed Precision Kuan Wang, Zhijian Liu, Yujun Lin, Ji Lin, Song Han 2018-11-21 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) - 701 + 706 @@ -776,13 +776,13 @@

3. Most cited articles on Latent Space Simulator Variants of Dynamic Mode Decomposition: Boundary Condition, Koopman, and Fourier Analyses Kevin K. Chen, Jonathan H. Tu, C. Rowley 2012-04-27 Journal of Nonlinear Science - 646 + 648 @@ -798,13 +798,13 @@

3. Most cited articles on Latent Space Simulator Cholesterol sensor ORP1L contacts the ER protein VAP to control Rab7–RILP–p150Glued and late endosome positioning Nuno Rocha, C. Kuijl, Rik van der Kant, L. Janssen, D. Houben, H. Janssen, W. Zwart, J. Neefjes 2009-06-29 The Journal of Cell Biology - 622 + 623 @@ -820,24 +820,24 @@

3. Most cited articles on Latent Space Simulator Proxy prefix caching for multimedia streams S. Sen, J. Rexford, D. Towsley 1999-03-21 IEEE INFOCOM '99. Conference on Computer Communications. Proceedings. Eighteenth Annual Joint Conference of the IEEE Computer and Communications Societies. The Future is Now (Cat. No.99CH36320) - 596 + 597 Causal Effect Inference with Deep Latent-Variable Models Christos Louizos, Uri Shalit, J. Mooij, D. Sontag, R. Zemel, Max Welling 2017-05-24 Neural Information Processing Systems - 582 + 587 @@ -900,7 +900,7 @@

3. Most cited articles on Latent Space Simulator Impairments in High-Frequency Transmission, Synaptic Vesicle Docking, and Synaptic Protein Distribution in the Hippocampus of BDNF Knockout Mice - L. Pozzo-Miller, W. Gottschalk, Li Zhang, Kathryn McDermott, J. Du, R. Gopalakrishnan, C. Oho, Z. Sheng, B. Lu + L. Pozzo-Miller, W. Gottschalk, Li Zhang, Kathryn McDermott, J. Du, R. Gopalakrishnan, C. Oho, Zu-Hang Sheng, B. Lu 1999-06-15 The Journal of Neuroscience 489 @@ -919,13 +919,13 @@

3. Most cited articles on Latent Space Simulator Boltzmann generators: Sampling equilibrium states of many-body systems with deep learning F. Noé, Jonas Köhler, Hao Wu 2019-09-05 Science - 471 + 474 @@ -952,78 +952,78 @@

3. Most cited articles on Latent Space Simulator - Structure and function of tetanus and botulinum neurotoxins - Cesare Montecucco, Giampietro Schiavo - 1995-11-01 - Quarterly Reviews of Biophysics - 442 + VAMPnets for deep learning of molecular kinetics + Andreas Mardt, Luca Pasquali, Hao Wu, F. Noé + 2017-10-16 + Nature Communications + 445 - VAMPnets for deep learning of molecular kinetics - Andreas Mardt, Luca Pasquali, Hao Wu, F. Noé - 2017-10-16 - Nature Communications + Structure and function of tetanus and botulinum neurotoxins + Cesare Montecucco, Giampietro Schiavo + 1995-11-01 + Quarterly Reviews of Biophysics 442 Koopman Invariant Subspaces and Finite Linear Representations of Nonlinear Dynamical Systems for Control S. Brunton, Bingni W. Brunton, J. Proctor, J. Kutz 2015-10-11 PLoS ONE - 438 + 439 Co-option of a default secretory pathway for plant immune responses Chian Kwon, C. Neu, Simone Pajonk, H. Yun, Ulrike Lipka, M. Humphry, Stefan Bau, Marco R. Straus, Mark Kwaaitaal, Heike Rampelt, F. Kasmi, G. Jürgens, J. Parker, R. Panstruga, V. Lipka, P. Schulze-Lefert 2008-02-14 Nature - 430 + 431 Learning effective human pose estimation from inaccurate annotation Sam Johnson, M. Everingham 2011-06-20 CVPR 2011 - 425 + 426 - SNARE proteins are highly enriched in lipid rafts in PC12 cells: Implications for the spatial control of exocytosis - L. Chamberlain, R. Burgoyne, G. Gould - 2001-05-01 - Proceedings of the National Academy of Sciences of the United States of America - 416 + Triple Generative Adversarial Nets + Chongxuan Li, T. Xu, Jun Zhu, Bo Zhang + 2017-03-07 + ArXiv + 417 - Triple Generative Adversarial Nets - Chongxuan Li, T. Xu, Jun Zhu, Bo Zhang - 2017-03-07 - ArXiv + SNARE proteins are highly enriched in lipid rafts in PC12 cells: Implications for the spatial control of exocytosis + L. Chamberlain, R. Burgoyne, G. Gould + 2001-05-01 + Proceedings of the National Academy of Sciences of the United States of America 416 @@ -1040,13 +1040,13 @@

3. Most cited articles on Latent Space Simulator Identification of the nerve terminal targets of botulinum neurotoxin serotypes A, D, and E. G. Schiavo, O. Rossetto, Stefan Catsicas, P. P. Laureto, B. Dasgupta, F. Benfenati, C. Montecucco 1993-11-15 The Journal of biological chemistry - 397 + 398 @@ -1073,24 +1073,24 @@

3. Most cited articles on Latent Space Simulator Estimating a State-Space Model from Point Process Observations Anne C. Smith, E. Brown 2003-05-01 Neural Computation - 377 + 378 Endothelial Caveolae Have the Molecular Transport Machinery for Vesicle Budding, Docking, and Fusion Including VAMP, NSF, SNAP, Annexins, and GTPases (*) J. Schnitzer, Jun Liu, P. Oh 1995-06-16 The Journal of Biological Chemistry - 368 + 370 @@ -1098,7 +1098,7 @@

3. Most cited articles on Latent Space Simulator Calcium-dependent interaction of N-type calcium channels with the synaptic core complex - Z. Sheng, J. Rettig, Terry Cook, W. Catterall + Zu-Hang Sheng, J. Rettig, Terry Cook, W. Catterall 1996-02-01 Nature 360 @@ -1139,12 +1139,23 @@

3. Most cited articles on Latent Space Simulator Ergodic Theory, Dynamic Mode Decomposition, and Computation of Spectral Properties of the Koopman Operator Hassan Arbabi, I. Mezić 2016-11-21 SIAM J. Appl. Dyn. Syst. + 340 + + + + + Align Your Latents: High-Resolution Video Synthesis with Latent Diffusion Models + A. Blattmann, Robin Rombach, Huan Ling, Tim Dockhorn, Seung Wook Kim, S. Fidler, Karsten Kreis + 2023-04-18 + 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 339 @@ -1161,45 +1172,45 @@

3. Most cited articles on Latent Space Simulator Deep Fluids: A Generative Network for Parameterized Fluid Simulations Byungsoo Kim, V. C. Azevedo, N. Thürey, Theodore Kim, M. Gross, B. Solenthaler 2018-06-06 Computer Graphics Forum - 335 + 336 Assessment: Botulinum neurotoxin for the treatment of spasticity (an evidence-based review): Report of the Therapeutics and Technology Assessment Subcommittee of the American Academy of NeurologySYMBOL D. Simpson, J. Gracies, H. Graham, J. Miyasaki, M. Naumann, B. Russman, L. Simpson, Y. So 2008-05-06 Neurology - 333 + 332 - Align Your Latents: High-Resolution Video Synthesis with Latent Diffusion Models - A. Blattmann, Robin Rombach, Huan Ling, Tim Dockhorn, Seung Wook Kim, S. Fidler, Karsten Kreis - 2023-04-18 - 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) - 330 + Predicting Short-Term Traffic Flow by Long Short-Term Memory Recurrent Neural Network + Yongxue Tian, Li Pan + 2015-12-01 + 2015 IEEE International Conference on Smart City/SocialCom/SustainCom (SmartCity) + 328 - Predicting Short-Term Traffic Flow by Long Short-Term Memory Recurrent Neural Network - Yongxue Tian, Li Pan - 2015-12-01 - 2015 IEEE International Conference on Smart City/SocialCom/SustainCom (SmartCity) + Dynamics-Aware Unsupervised Discovery of Skills + Archit Sharma, S. Gu, S. Levine, Vikash Kumar, Karol Hausman + 2019-07-02 + ArXiv 327 @@ -1214,17 +1225,6 @@

3. Most cited articles on Latent Space Simulator327 - - - Dynamics-Aware Unsupervised Discovery of Skills - Archit Sharma, S. Gu, S. Levine, Vikash Kumar, Karol Hausman - 2019-07-02 - ArXiv - 326 - - Extended dynamic mode decomposition with dictionary learning: A data-driven adaptive spectral decomposition of the Koopman operator. Qianxiao Li, Felix Dietrich, E. Bollt, I. Kevrekidis 2017-07-02 Chaos - 323 + 324 + + + + + Time-lagged autoencoders: Deep learning of slow collective variables for molecular kinetics + C. Wehmeyer, F. Noé + 2017-10-30 + The Journal of chemical physics + 319 @@ -1269,17 +1280,6 @@

3. Most cited articles on Latent Space Simulator319 - - - Time-lagged autoencoders: Deep learning of slow collective variables for molecular kinetics - C. Wehmeyer, F. Noé - 2017-10-30 - The Journal of chemical physics - 317 - - + Botulinum neurotoxin serotype F is a zinc endopeptidase specific for VAMP/synaptobrevin. + G. Schiavo, C. Shone, O. Rossetto, F. Alexander, C. Montecucco + 1993-06-05 + The Journal of biological chemistry + 312 + + - Virtual network functions placement and routing optimization - B. Addis, Dallal Belabed, M. Bouet, Stefano Secci - 2015-10-05 - 2015 IEEE 4th International Conference on Cloud Networking (CloudNet) + Learning Deep Neural Network Representations for Koopman Operators of Nonlinear Dynamical Systems + Enoch Yeung, Soumya Kundu, Nathan Oken Hodas + 2017-08-22 + 2019 American Control Conference (ACC) 311 @@ -1339,44 +1350,44 @@

3. Most cited articles on Latent Space Simulator // alert (311) - Botulinum neurotoxin serotype F is a zinc endopeptidase specific for VAMP/synaptobrevin. - G. Schiavo, C. Shone, O. Rossetto, F. Alexander, C. Montecucco - 1993-06-05 - The Journal of biological chemistry + Virtual network functions placement and routing optimization + B. Addis, Dallal Belabed, M. Bouet, Stefano Secci + 2015-10-05 + 2015 IEEE 4th International Conference on Cloud Networking (CloudNet) 311 Adaptive cache compression for high-performance processors Alaa R. Alameldeen, D. Wood 2004-06-19 Proceedings. 31st Annual International Symposium on Computer Architecture, 2004. - 310 + 311 PYIN: A fundamental frequency estimator using probabilistic threshold distributions Matthias Mauch, S. Dixon 2014-05-04 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) - 306 + 308 - Learning Deep Neural Network Representations for Koopman Operators of Nonlinear Dynamical Systems - Enoch Yeung, Soumya Kundu, Nathan Oken Hodas - 2017-08-22 - 2019 American Control Conference (ACC) - 306 + Beyond 5G With UAVs: Foundations of a 3D Wireless Cellular Network + Mohammad Mozaffari, Ali Taleb Zadeh Kasgari, W. Saad, M. Bennis, M. Debbah + 2018-05-16 + IEEE Transactions on Wireless Communications + 305 @@ -1392,24 +1403,13 @@

3. Most cited articles on Latent Space Simulator - Beyond 5G With UAVs: Foundations of a 3D Wireless Cellular Network - Mohammad Mozaffari, Ali Taleb Zadeh Kasgari, W. Saad, M. Bennis, M. Debbah - 2018-05-16 - IEEE Transactions on Wireless Communications - 304 - - - - Meta-Reinforcement Learning of Structured Exploration Strategies Abhishek Gupta, Russell Mendonca, Yuxuan Liu, P. Abbeel, S. Levine 2018-02-20 Neural Information Processing Systems - 300 + 302 @@ -1423,6 +1423,17 @@

3. Most cited articles on Latent Space Simulator300 + + + Integrated transcriptional and competitive endogenous RNA networks are cross-regulated in permissive molecular environments + U. Ala, F. Karreth, C. Bosia, A. Pagnani, R. Taulli, Valentine Léopold, Yvonne Tay, P. Provero, R. Zecchina, P. Pandolfi + 2013-03-27 + Proceedings of the National Academy of Sciences + 300 + + - Integrated transcriptional and competitive endogenous RNA networks are cross-regulated in permissive molecular environments - U. Ala, F. Karreth, C. Bosia, A. Pagnani, R. Taulli, Valentine Léopold, Yvonne Tay, P. Provero, R. Zecchina, P. Pandolfi - 2013-03-27 - Proceedings of the National Academy of Sciences - 298 - - On Convergence of Extended Dynamic Mode Decomposition to the Koopman Operator Milan Korda, I. Mezić 2017-03-14 Journal of Nonlinear Science - 292 + 293 Calcium accelerates endocytosis of vSNAREs at hippocampal synapses S. Sankaranarayanan, T. A. Ryan 2001-02-01 Nature Neuroscience - 291 + 290 @@ -1524,46 +1524,46 @@

3. Most cited articles on Latent Space Simulator - A SNARE complex mediating fusion of late endosomes defines conserved properties of SNARE structure and function - Wolfram Antonin, Claudia Holroyd, D. Fasshauer, Stefan Pabst, G. F. von Mollard, R. Jahn - 2000-12-01 - The EMBO Journal - 277 + Molecular generative model based on conditional variational autoencoder for de novo molecular design + Jaechang Lim, Seongok Ryu, Jin Woo Kim, W. Kim + 2018-06-15 + Journal of Cheminformatics + 278 - Syntaxin 13 Mediates Cycling of Plasma Membrane Proteins via Tubulovesicular Recycling Endosomes - R. Prekeris, J. Klumperman, Yu A. Chen, R. Scheller - 1998-11-16 - The Journal of Cell Biology - 277 + Tetanus and botulinum neurotoxins: mechanism of action and therapeutic uses. + R. Pellizzari, O. Rossetto, G. Schiavo, C. Montecucco + 1999-02-28 + Philosophical transactions of the Royal Society of London. Series B, Biological sciences + 278 - Molecular generative model based on conditional variational autoencoder for de novo molecular design - Jaechang Lim, Seongok Ryu, Jin Woo Kim, W. Kim - 2018-06-15 - Journal of Cheminformatics - 276 + Syntaxin 13 Mediates Cycling of Plasma Membrane Proteins via Tubulovesicular Recycling Endosomes + R. Prekeris, J. Klumperman, Yu A. Chen, R. Scheller + 1998-11-16 + The Journal of Cell Biology + 278 - Tetanus and botulinum neurotoxins: mechanism of action and therapeutic uses. - R. Pellizzari, O. Rossetto, G. Schiavo, C. Montecucco - 1999-02-28 - Philosophical transactions of the Royal Society of London. Series B, Biological sciences - 276 + A SNARE complex mediating fusion of late endosomes defines conserved properties of SNARE structure and function + Wolfram Antonin, Claudia Holroyd, D. Fasshauer, Stefan Pabst, G. F. von Mollard, R. Jahn + 2000-12-01 + The EMBO Journal + 277 @@ -1577,6 +1577,17 @@

3. Most cited articles on Latent Space Simulator274 + + + T-Lohi: A New Class of MAC Protocols for Underwater Acoustic Sensor Networks + A. Syed, W. Ye, J. Heidemann + 2008-04-13 + IEEE INFOCOM 2008 - The 27th Conference on Computer Communications + 274 + + - T-Lohi: A New Class of MAC Protocols for Underwater Acoustic Sensor Networks - A. Syed, W. Ye, J. Heidemann - 2008-04-13 - IEEE INFOCOM 2008 - The 27th Conference on Computer Communications - 273 + Deep Collaborative Embedding for Social Image Understanding + Zechao Li, Jinhui Tang, Tao Mei + 2019-09-01 + IEEE Transactions on Pattern Analysis and Machine Intelligence + 271 @@ -1613,23 +1624,12 @@

3. Most cited articles on Latent Space Simulator - Deep Collaborative Embedding for Social Image Understanding - Zechao Li, Jinhui Tang, Tao Mei - 2019-09-01 - IEEE Transactions on Pattern Analysis and Machine Intelligence - 270 - - - - Clinical information for research; the use of general practice databases. R. Lawrenson, T. Williams, Richard D.T. Farmer 1999-09-01 Journal of public health medicine - 269 + 270 @@ -1658,55 +1658,55 @@

3. Most cited articles on Latent Space Simulator // alert (261) - Application of Unidimensional Item Response Theory Models to Multidimensional Data - F. Drasgow, C. Parsons - 1983-04-01 - Applied Psychological Measurement + The Vesiculo–Vacuolar Organelle (VVO): A New Endothelial Cell Permeability Organelle + A. Dvorak, Dian Feng + 2001-04-01 + Journal of Histochemistry & Cytochemistry 261 The spread of attention across modalities and space in a multisensory object. L. Busse, K. Roberts, R. Crist, D. Weissman, M. Woldorff 2005-12-20 Proceedings of the National Academy of Sciences of the United States of America - 260 + 261 - The Vesiculo–Vacuolar Organelle (VVO): A New Endothelial Cell Permeability Organelle - A. Dvorak, Dian Feng - 2001-04-01 - Journal of Histochemistry & Cytochemistry - 259 + Application of Unidimensional Item Response Theory Models to Multidimensional Data + F. Drasgow, C. Parsons + 1983-04-01 + Applied Psychological Measurement + 261 Cleavage of members of the synaptobrevin/VAMP family by types D and F botulinal neurotoxins and tetanus toxin. Shiqji YamasakiSg, Anja BaumeisterS, Thomas BinzS, Juan Blasi, Egenhard Linkfi, Fabrice Cornillell, Bernard Roquesll, E. Fykse, Thomas, SudhoP, Reinhard Jahnn, Heiner NiemannS 1994-04-29 The Journal of biological chemistry - 259 + 260 Synaptophysin, a major synaptic vesicle protein, is not essential for neurotransmitter release. Harvey T. McMahon, Harvey T. McMahon, Vadim Y. Bolshakov, R. Janz, Robert E. Hammer, S. Siegelbaum, Thomas C. Südhof 1996-05-14 Proceedings of the National Academy of Sciences of the United States of America - 258 + 259 @@ -1749,6 +1749,54 @@

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+ + Multi-Agent Deep Reinforcement Learning for Spectral Efficiency Optimization in Vehicular Optical Camera Communications + Amirul Islam, N. Thomos, Leila Musavian + 2024-05-01 + IEEE Transactions on Mobile Computing + 1 + + + + Dynamic RAN Slicing Mapping Under the Sliding Scheduled Traffic Model Based on Deep Reinforcement Learning in Elastic Optical Networks + Yunwu Wang, Lingxing Kong, M. Zhu, Jiahua Gu, Xiang Liu, Weidong Tong, B. Hua, M. Lei, Yuancheng Cai, Jiao Zhang + 2024-04-15 + Journal of Lightwave Technology + 0 + + + + Shared Manifold Regularized Joint Feature Selection for Joint Classification and Regression in Alzheimer's Disease Diagnosis. + Zhi Chen, Yongguo Liu, Yun Zhang, Jiajing Zhu, Qiaoqin Li, Xindong Wu + 2024-04-04 + IEEE transactions on image processing : a publication of the IEEE Signal Processing Society + 0 + + + + Exploiting a variational auto-encoder to represent the evolution of sudden stratospheric warmings + Yi-Chang Chen, Yu‐Chiao Liang, Chien-Ming Wu, Jin-De Huang, Simon H Lee, Yih Wang, Yi-Jhen Zeng + 2024-04-03 + Environmental Research: Climate + 0 + + + + Blockchain Based Decentralized and Proactive Caching Strategy in Mobile Edge Computing Environment + Jingpan Bai, Silei Zhu, Houling Ji + 2024-04-03 + Sensors + 0 + + + + NeRF-Texture: Synthesizing Neural Radiance Field Textures. + Yihua Huang, Yan-Pei Cao, Yu-Kun Lai, Ying Shan, Lin Gao + 2024-04-02 + IEEE transactions on pattern analysis and machine intelligence + 0 + + A Two-Stage Multi-Target Domain Adaptation Framework for Prediction of Key Performance Indicators Based on Adversarial Network Cheng Su, Xin Peng, Dan Yang, Zhi Li, Xiaolong Wu, Weimin Zhong @@ -1781,6 +1829,14 @@

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0 + + Space wandering in the rodent default mode network. + T. Nghiem, Byeongwook Lee, T. Chao, Nicholas K. Branigan, Percy K Mistry, Yen-Yu Ian Shih, Vinod Menon + 2024-04-01 + Proceedings of the National Academy of Sciences of the United States of America + 0 + + MS-CLS: An Effective Partitioning and Placement Metaheuristic for Wafer-Scale Physics Modeling Canhui Luo, Zhouxing Su, Zhipeng Lü @@ -1805,6 +1861,14 @@

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0 + + IML-Net: A Framework for Cross-View Geo-Localization with Multi-Domain Remote Sensing Data + Yiming Yan, Mengyuan Wang, Nan Su, Wei Hou, Chunhui Zhao, Wenxuan Wang + 2024-03-31 + Remote Sensing + 0 + + Toward the Usage of Deep Learning Surrogate Models in Ground Vehicle Aerodynamics Benet Eiximeno, Arnau Miró, Ivette Rodríguez, O. Lehmkuhl @@ -1815,7 +1879,7 @@

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Recurrent variational autoencoder approach for remaining useful life estimation - N. Costa, Luciano Sánchez + N. Costa, L. Sánchez 2024-03-26 Logic Journal of the IGPL 0 @@ -1885,6 +1949,14 @@

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0 + + High-Temperature Tolerance Protein Engineering through Deep Evolution + Huanyu Chu, Zhenyang Tian, Lingling Hu, Hejian Zhang, Hong Chang, Jie Bai, Dingyu Liu, Lina Lu, Jian Cheng, Huifeng Jiang + 2024-03-20 + Biodesign Research + 0 + + MagGen: A Graph-Aided Deep Generative Model for Inverse Design of Permanent Magnets. Sourav Mal, Gaurav Seal, Prasenjit Sen @@ -1917,6 +1989,38 @@

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0 + + Optimization of Pressure Management Strategies for Geological CO2 Sequestration Using Surrogate Model-based Reinforcement Learning + Jungang Chen, Eduardo Gildin, Georgy Kompantsev + 2024-03-12 + ArXiv + 0 + + + + DiffuMatting: Synthesizing Arbitrary Objects with Matting-level Annotation + Xiaobin Hu, Xu Peng, Donghao Luo, Xiaozhong Ji, Jinlong Peng, Zhengkai Jiang, Jiangning Zhang, Taisong Jin, Chengjie Wang, Rongrong Ji + 2024-03-10 + ArXiv + 0 + + + + tLaSDI: Thermodynamics-informed latent space dynamics identification + Jun Sur Richard Park, Siu Wun Cheung, Youngsoo Choi, Yeonjong Shin + 2024-03-09 + ArXiv + 1 + + + + Large Generative Model Assisted 3D Semantic Communication + Feibo Jiang, Yubo Peng, Li Dong, Kezhi Wang, Kun Yang, Cunhua Pan, Xiaohu You + 2024-03-09 + ArXiv + 0 + + Access authentication via blockchain in space information network Muhammad Arshad, Jianwei Liu, Muhammad Khalid, Waqar Khalid, Yue Cao, Fakhri Alam Khan @@ -1925,6 +2029,14 @@

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0 + + Behavior Generation with Latent Actions + Seungjae Lee, Yibin Wang, Haritheja Etukuru, H. J. Kim, Nur Muhammad, Mahi Shafiullah, Lerrel Pinto + 2024-03-05 + ArXiv + 0 + + Small molecule autoencoders: architecture engineering to optimize latent space utility and sustainability Marie Oestreich, Iva Ewert, Matthias Becker @@ -1949,6 +2061,14 @@

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0 + + Deep Incremental Model Based Reinforcement Learning: A One-Step Lookback Approach for Continuous Robotics Control + Cong Li + 2024-03-03 + ArXiv + 0 + + Topic Modeling on Document Networks With Dirichlet Optimal Transport Barycenter Delvin Ce Zhang, Hady W. Lauw @@ -1981,6 +2101,14 @@

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0 + + LoMOE: Localized Multi-Object Editing via Multi-Diffusion + Goirik Chakrabarty, Aditya Chandrasekar, Ramya Hebbalaguppe, AP Prathosh + 2024-03-01 + ArXiv + 0 + + Learning-Based Edge-Device Collaborative DNN Inference in IoVT Networks Xiaodong Xu, Kaiwen Yan, Shujun Han, Bizhu Wang, Xiaofeng Tao, Ping Zhang @@ -2201,7 +2329,7 @@

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Modeling and Simulating an Epidemic in Two Dimensions with an Application Regarding COVID-19 Khalaf M. Alanazi 2024-02-12 - Computation + Comput. 0 @@ -2210,12 +2338,12 @@

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Shengxiang Hu, Guobing Zou, Song Yang, Yanglan Gan, Bofeng Zhang, Yixin Chen 2024-02-08 ArXiv - 0 + 1 Language uncovers visuospatial dysfunction in posterior cortical atrophy: a natural language processing approach - N. Rezaii, D. Hochberg, M. Quimby, Bonnie Wong, Scott McGinnis, Bradford C. Dickerson, D. Putcha + N. Rezaii, D. Hochberg, M. Quimby, Bonnie Wong, Scott McGinnis, Bradford C Dickerson, D. Putcha 2024-02-06 Frontiers in Neuroscience 0 @@ -2226,7 +2354,7 @@

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Kun Wang, Hao Wu, Guibin Zhang, Junfeng Fang, Yuxuan Liang, Yuankai Wu, Roger Zimmermann, Yang Wang 2024-02-06 ArXiv - 2 + 3 @@ -2386,12 +2514,12 @@

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Quentin Anthony, Yury Tokpanov, Paolo Glorioso, Beren Millidge 2024-02-01 ArXiv - 3 + 2 Discriminative Action Snippet Propagation Network for Weakly Supervised Temporal Action Localization - Yuanjie Dang, Chunxia Huang, Peng Chen, Dongdong Zhao, Nan Gao, Ronghua Liang, Ruohong Huan + Yuanjie Dang, Chunxia Huang, Peng Chen, Dongdong Zhao, Nan Gao, Ronghua Liang, R. Huan 2024-01-31 ACM Transactions on Multimedia Computing, Communications, and Applications 0 @@ -2421,134 +2549,6 @@

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@@ -2558,14 +2558,14 @@

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Neural Ordinary Differential Equations T. Chen, Yulia Rubanova, J. Bettencourt, D. Duvenaud 2018-06-19 Neural Information Processing Systems - 3601 + 3624 Score-Based Generative Modeling through Stochastic Differential Equations Yang Song, Jascha Narain Sohl-Dickstein, Diederik P. Kingma, Abhishek Kumar, Stefano Ermon, Ben Poole 2020-11-26 ArXiv - 2820 + 2851 Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting Yaguang Li, Rose Yu, C. Shahabi, Yan Liu 2017-07-06 arXiv: Learning - 2173 + 2191 Artificial neural networks for solving ordinary and partial differential equations I. Lagaris, A. Likas, D. Fotiadis 1997-05-19 IEEE transactions on neural networks - 1743 + 1753 Diffusion-Convolutional Neural Networks James Atwood, D. Towsley 2015-11-06 Neural Information Processing Systems - 1096 + 1105 Dynamic Edge-Conditioned Filters in Convolutional Neural Networks on Graphs M. Simonovsky, N. Komodakis 2017-04-10 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) - 1081 + 1087 FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative Models Will Grathwohl, Ricky T. Q. Chen, J. Bettencourt, I. Sutskever, D. Duvenaud 2018-09-27 ArXiv - 695 + 699 Stable architectures for deep neural networks E. Haber, Lars Ruthotto 2017-05-09 Inverse Problems - 601 + 605 DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps Cheng Lu, Yuhao Zhou, Fan Bao, Jianfei Chen, Chongxuan Li, Jun Zhu 2022-06-02 ArXiv - 551 + 563 - Brian: A Simulator for Spiking Neural Networks in Python - Dan F. M. Goodman, Romain Brette - 2008-07-11 - Frontiers in Neuroinformatics - 526 + Diffusion Improves Graph Learning + Johannes Klicpera, Stefan Weißenberger, Stephan Günnemann + 2019-10-28 + Neural Information Processing Systems + 502 Augmented Neural ODEs Emilien Dupont, A. Doucet, Y. Teh 2019-04-02 ArXiv - 500 + 501 - Diffusion Improves Graph Learning - Johannes Klicpera, Stefan Weißenberger, Stephan Günnemann - 2019-10-28 - Neural Information Processing Systems - 496 - - - - Geometric Matrix Completion with Recurrent Multi-Graph Neural Networks Federico Monti, M. Bronstein, X. Bresson 2017-04-01 Neural Information Processing Systems - 470 + 472 Neural Operator: Graph Kernel Network for Partial Differential Equations Zong-Yi Li, Nikola B. Kovachki, K. Azizzadenesheli, Burigede Liu, K. Bhattacharya, Andrew M. Stuart, Anima Anandkumar 2020-02-26 ArXiv - 462 + 465 @@ -798,24 +787,24 @@

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Beyond Finite Layer Neural Networks: Bridging Deep Architectures and Numerical Differential Equations Yiping Lu, Aoxiao Zhong, Quanzheng Li, Bin Dong 2017-10-27 ArXiv - 433 + 434 Latent Ordinary Differential Equations for Irregularly-Sampled Time Series Yulia Rubanova, T. Chen, D. Duvenaud None Neural Information Processing Systems - 424 + 427 @@ -831,13 +820,13 @@

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Rumor Detection on Social Media with Bi-Directional Graph Convolutional Networks Tian Bian, Xi Xiao, Tingyang Xu, P. Zhao, Wenbing Huang, Yu Rong, Junzhou Huang 2020-01-17 AAAI Conference on Artificial Intelligence - 389 + 394 @@ -853,13 +842,13 @@

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Neural Operator: Learning Maps Between Function Spaces Nikola B. Kovachki, Zong-Yi Li, Burigede Liu, K. Azizzadenesheli, K. Bhattacharya, Andrew M. Stuart, Anima Anandkumar 2021-08-19 ArXiv - 327 + 330 @@ -875,24 +864,24 @@

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Neural Controlled Differential Equations for Irregular Time Series Patrick Kidger, James Morrill, James Foster, Terry Lyons 2020-05-18 ArXiv - 313 + 315 SIGN: Scalable Inception Graph Neural Networks Emanuele Rossi, Fabrizio Frasca, B. Chamberlain, D. Eynard, M. Bronstein, Federico Monti 2020-04-23 ArXiv - 291 + 295 @@ -908,35 +897,35 @@

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Multipole Graph Neural Operator for Parametric Partial Differential Equations Zong-Yi Li, Nikola B. Kovachki, K. Azizzadenesheli, Burigede Liu, K. Bhattacharya, Andrew M. Stuart, Anima Anandkumar 2020-06-16 ArXiv - 256 + 258 Scalable Gradients for Stochastic Differential Equations Xuechen Li, Ting-Kam Leonard Wong, Ricky T. Q. Chen, D. Duvenaud 2020-01-05 ArXiv - 239 + 243 Reversible Architectures for Arbitrarily Deep Residual Neural Networks B. Chang, Lili Meng, E. Haber, Lars Ruthotto, David Begert, E. Holtham 2017-09-12 AAAI Conference on Artificial Intelligence - 235 + 236 @@ -952,13 +941,13 @@

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Spina bifida Dr. R. Mühl-Benninghaus 2018-07-09 Der Radiologe - 223 + 224 @@ -1007,24 +996,24 @@

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Neural Jump Stochastic Differential Equations J. Jia, Austin R. Benson 2019-05-24 ArXiv - 181 + 183 Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow Xingchao Liu, Chengyue Gong, Qiang Liu 2022-09-07 ArXiv - 178 + 179 @@ -1051,46 +1040,46 @@

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- Systems biology informed deep learning for inferring parameters and hidden dynamics - A. Yazdani, Lu Lu, M. Raissi, G. Karniadakis - 2019-12-04 - PLoS Computational Biology - 172 - - - - - AntisymmetricRNN: A Dynamical System View on Recurrent Neural Networks - B. Chang, Minmin Chen, E. Haber, Ed H. Chi - 2019-02-26 + GRAND: Graph Neural Diffusion + B. Chamberlain, J. Rowbottom, Maria I. Gorinova, Stefan Webb, Emanuele Rossi, M. Bronstein + 2021-06-21 ArXiv - 171 + 175 DiffNet++: A Neural Influence and Interest Diffusion Network for Social Recommendation Le Wu, Junwei Li, Peijie Sun, Richang Hong, Yong Ge, Meng Wang 2020-01-15 IEEE Transactions on Knowledge and Data Engineering - 170 + 173 - GRAND: Graph Neural Diffusion - B. Chamberlain, J. Rowbottom, Maria I. Gorinova, Stefan Webb, Emanuele Rossi, M. Bronstein - 2021-06-21 + AntisymmetricRNN: A Dynamical System View on Recurrent Neural Networks + B. Chang, Minmin Chen, E. Haber, Ed H. Chi + 2019-02-26 ArXiv - 166 + 172 + + + + + Systems biology informed deep learning for inferring parameters and hidden dynamics + A. Yazdani, Lu Lu, M. Raissi, G. Karniadakis + 2019-12-04 + PLoS Computational Biology + 172 @@ -1117,13 +1106,13 @@

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HiPPO: Recurrent Memory with Optimal Polynomial Projections Albert Gu, Tri Dao, Stefano Ermon, A. Rudra, C. Ré 2020-08-17 ArXiv - 163 + 165 @@ -1137,6 +1126,17 @@

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158 + + + Combining Differentiable PDE Solvers and Graph Neural Networks for Fluid Flow Prediction + Filipe de Avila Belbute-Peres, T. Economon, J. Z. Kolter + 2020-07-08 + International Conference on Machine Learning + 158 + + - Combining Differentiable PDE Solvers and Graph Neural Networks for Fluid Flow Prediction - Filipe de Avila Belbute-Peres, T. Economon, J. Z. Kolter - 2020-07-08 - International Conference on Machine Learning - 156 + Spectral-approximation-based intelligent modeling for distributed thermal processes + H. Deng, Han-Xiong Li, Guanrong Chen + 2005-08-29 + IEEE Transactions on Control Systems Technology + 155 @@ -1170,17 +1170,6 @@

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154 - - - Spectral-approximation-based intelligent modeling for distributed thermal processes - H. Deng, Han-Xiong Li, Guanrong Chen - 2005-08-29 - IEEE Transactions on Control Systems Technology - 154 - - ANODE: Unconditionally Accurate Memory-Efficient Gradients for Neural ODEs A. Gholami, K. Keutzer, G. Biros 2019-02-27 ArXiv - 145 + 147 The development of the human brain, the closure of the caudal neuropore, and the beginning of secondary neurulation at stage 12 F. Müller, R. O'rahilly None Anatomy and Embryology - 140 + 141 @@ -1249,13 +1238,13 @@

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On Neural Differential Equations Patrick Kidger 2022-02-04 ArXiv - 133 + 134 @@ -1280,6 +1269,17 @@

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131 + + + Graph Neural Controlled Differential Equations for Traffic Forecasting + Jeongwhan Choi, Hwangyong Choi, JeeHyun Hwang, Noseong Park + 2021-12-07 + ArXiv + 130 + + - Graph Neural Controlled Differential Equations for Traffic Forecasting - Jeongwhan Choi, Hwangyong Choi, JeeHyun Hwang, Noseong Park - 2021-12-07 - ArXiv - 126 - - + Traffic Flow Forecasting with Spatial-Temporal Graph Diffusion Network + Xiyue Zhang, Chao Huang, Yong Xu, Lianghao Xia, Peng Dai, Liefeng Bo, Junbo Zhang, Yu Zheng + 2021-05-18 + AAAI Conference on Artificial Intelligence + 123 + + + + Runge-Kutta neural network for identification of dynamical systems in high accuracy Yi-Jen Wang, Chin-Teng Lin 1998-03-01 IEEE transactions on neural networks - 122 + 123 @@ -1346,17 +1346,6 @@

3. Most cited articles on Neural ODEs

121 - - - Traffic Flow Forecasting with Spatial-Temporal Graph Diffusion Network - Xiyue Zhang, Chao Huang, Yong Xu, Lianghao Xia, Peng Dai, Liefeng Bo, Junbo Zhang, Yu Zheng - 2021-05-18 - AAAI Conference on Artificial Intelligence - 121 - - + On Robustness of Neural Ordinary Differential Equations + Hanshu Yan, Jiawei Du, V. Tan, Jiashi Feng + 2019-10-12 + ArXiv + 114 + + + + A Comparison of Automatic Differentiation and Continuous Sensitivity Analysis for Derivatives of Differential Equation Solutions Christopher Rackauckas, Yingbo Ma, Vaibhav Dixit, Xingjian Guo, Mike Innes, Jarrett Revels, J. Nyberg, V. Ivaturi 2018-12-05 2021 IEEE High Performance Extreme Computing Conference (HPEC) - 113 + 112 - On Robustness of Neural Ordinary Differential Equations - Hanshu Yan, Jiawei Du, V. Tan, Jiashi Feng - 2019-10-12 - ArXiv - 113 + Continuous Graph Neural Networks + Louis-Pascal Xhonneux, Meng Qu, Jian Tang + 2019-12-02 + International Conference on Machine Learning + 110 + + + + + E(n) Equivariant Normalizing Flows + Victor Garcia Satorras, Emiel Hoogeboom, F. Fuchs, I. Posner, M. Welling + 2021-05-19 + Neural Information Processing Systems + 108 @@ -1425,22 +1436,22 @@

3. Most cited articles on Neural ODEs

- E(n) Equivariant Normalizing Flows - Victor Garcia Satorras, Emiel Hoogeboom, F. Fuchs, I. Posner, M. Welling - 2021-05-19 - Neural Information Processing Systems - 107 + Neural SDE: Stabilizing Neural ODE Networks with Stochastic Noise + Xuanqing Liu, Tesi Xiao, Si Si, Qin Cao, Sanjiv Kumar, Cho-Jui Hsieh + 2019-06-05 + ArXiv + 106 - Neural SDE: Stabilizing Neural ODE Networks with Stochastic Noise - Xuanqing Liu, Tesi Xiao, Si Si, Qin Cao, Sanjiv Kumar, Cho-Jui Hsieh - 2019-06-05 + Graph Neural Ordinary Differential Equations + Michael Poli, Stefano Massaroli, Junyoung Park, A. Yamashita, H. Asama, Jinkyoo Park + 2019-11-18 ArXiv 106 @@ -1449,13 +1460,24 @@

3. Most cited articles on Neural ODEs

- Continuous Graph Neural Networks - Louis-Pascal Xhonneux, Meng Qu, Jian Tang - 2019-12-02 - International Conference on Machine Learning + Liquid Time-constant Networks + Ramin M. Hasani, Mathias Lechner, Alexander Amini, D. Rus, R. Grosu + 2020-06-08 + AAAI Conference on Artificial Intelligence 106 + + + DiffEqFlux.jl - A Julia Library for Neural Differential Equations + Christopher Rackauckas, Mike Innes, Yingbo Ma, J. Bettencourt, Lyndon White, Vaibhav Dixit + 2019-02-06 + ArXiv + 105 + + - DiffEqFlux.jl - A Julia Library for Neural Differential Equations - Christopher Rackauckas, Mike Innes, Yingbo Ma, J. Bettencourt, Lyndon White, Vaibhav Dixit - 2019-02-06 - ArXiv + Transfer Graph Neural Networks for Pandemic Forecasting + G. Panagopoulos, Giannis Nikolentzos, M. Vazirgiannis + 2020-09-10 + AAAI Conference on Artificial Intelligence 104 @@ -1526,31 +1548,20 @@

3. Most cited articles on Neural ODEs

- Graph Neural Ordinary Differential Equations - Michael Poli, Stefano Massaroli, Junyoung Park, A. Yamashita, H. Asama, Jinkyoo Park - 2019-11-18 + Monotone operator equilibrium networks + Ezra Winston, J. Z. Kolter + 2020-06-15 ArXiv 103 - - - Liquid Time-constant Networks - Ramin M. Hasani, Mathias Lechner, Alexander Amini, D. Rus, R. Grosu - 2020-06-08 - AAAI Conference on Artificial Intelligence - 103 - - - Monotone operator equilibrium networks - Ezra Winston, J. Z. Kolter - 2020-06-15 + SocialGCN: An Efficient Graph Convolutional Network based Model for Social Recommendation + Le Wu, Peijie Sun, Richang Hong, Yanjie Fu, Xiting Wang, M. Wang + 2018-11-07 ArXiv 102 @@ -1566,17 +1577,6 @@

3. Most cited articles on Neural ODEs

101 - - - SocialGCN: An Efficient Graph Convolutional Network based Model for Social Recommendation - Le Wu, Peijie Sun, Richang Hong, Yanjie Fu, Xiting Wang, M. Wang - 2018-11-07 - ArXiv - 101 - - - Transfer Graph Neural Networks for Pandemic Forecasting - G. Panagopoulos, Giannis Nikolentzos, M. Vazirgiannis - 2020-09-10 - AAAI Conference on Artificial Intelligence - 100 - - - - FOCNet: A Fractional Optimal Control Network for Image Denoising Xixi Jia, Sanyang Liu, Xiangchu Feng, Lei Zhang 2019-06-01 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) - 100 + 101 @@ -1634,13 +1623,13 @@

3. Most cited articles on Neural ODEs

Popularity Prediction on Social Platforms with Coupled Graph Neural Networks Qi Cao, Huawei Shen, Jinhua Gao, Bingzheng Wei, Xueqi Cheng 2019-06-21 Proceedings of the 13th International Conference on Web Search and Data Mining - 97 + 98 @@ -1654,6 +1643,17 @@

3. Most cited articles on Neural ODEs

95 + + + Neural Sheaf Diffusion: A Topological Perspective on Heterophily and Oversmoothing in GNNs + Cristian Bodnar, Francesco Di Giovanni, B. Chamberlain, Pietro Lio', Michael M. Bronstein + 2022-02-09 + ArXiv + 94 + + Adaptive Checkpoint Adjoint Method for Gradient Estimation in Neural ODE Juntang Zhuang, N. Dvornek, Xiaoxiao Li, S. Tatikonda, X. Papademetris, J. Duncan 2020-06-03 Proceedings of machine learning research - 90 + 91 - Extreme theory of functional connections: A fast physics-informed neural network method for solving ordinary and partial differential equations - E. Schiassi, R. Furfaro, Carl Leake, Mario De Florio, Hunter Johnston, D. Mortari - 2021-06-08 - Neurocomputing + Stiff Neural Ordinary Differential Equations + Suyong Kim, Weiqi Ji, Sili Deng, Chris Rackauckas + 2021-03-29 + Chaos 89 - Stiff Neural Ordinary Differential Equations - Suyong Kim, Weiqi Ji, Sili Deng, Chris Rackauckas - 2021-03-29 - Chaos - 88 + Extreme theory of functional connections: A fast physics-informed neural network method for solving ordinary and partial differential equations + E. Schiassi, R. Furfaro, Carl Leake, Mario De Florio, Hunter Johnston, D. Mortari + 2021-06-08 + Neurocomputing + 89 @@ -1749,6 +1749,62 @@

4. Latest articles on Neural ODEs

+ + Detection of wind turbine blade abnormalities through a deep learning model integrating VAE and neural ODE + Zeyun Yang, Mingqiang Xu, Shuqing Wang, Jun Li, Zhen Peng, Fei Jin, Yuan Yang + 2024-06-01 + Ocean Engineering + 0 + + + + Influence of Chemical and Radiation on an Unsteady MHD Oscillatory Flow using Artificial Neural Network (ANN) + R. Kavitha, M. Mahendran + 2024-04-02 + WSEAS TRANSACTIONS ON FLUID MECHANICS + 0 + + + + Forecasting with an N-dimensional Langevin equation and a neural-ordinary differential equation. + Antonio Malpica-Morales, M. Durán-Olivencia, S. Kalliadasis + 2024-04-01 + Chaos + 0 + + + + Dynamic Recommendation Based on Graph Diffusion and Ebbinghaus Curve + Zhihong Cui, Xiangguo Sun, Hongxu Chen, Li Pan, Li-zhen Cui, Shijun Liu, Guandong Xu + 2024-04-01 + IEEE Transactions on Computational Social Systems + 2 + + + + Spatial-temporal graph neural ODE networks for skeleton-based action recognition + Longji Pan, Jianguang Lu, Xianghong Tang + 2024-04-01 + Scientific Reports + 0 + + + + Multi-Wind Turbine Wind Speed Prediction Based on Weighted Diffusion Graph Convolution and Gated Attention Network + Yakai Qiao, Hui Chen, Bo Fu + 2024-03-30 + Energies + 0 + + + + Ultra-Short-Term Power Prediction of Large Offshore Wind Farms Based on Spatiotemporal Adaptation of Wind Turbines + Yuzheng An, Yongjun Zhang, Jianxi Lin, Yang Yi, Wei Fan, Zihan Cai + 2024-03-29 + Processes + 0 + + Predicting the thermal distribution in a convective wavy fin using a novel training physics-informed neural network method K. Chandan, Rania Saadeh, Ahmad Qazza, K. Karthik, R. S. Varun Kumar, R. N. Kumar, Umair Khan, Atef Masmoudi, M. M. M. Abdou, Walter Ojok, Raman Kumar @@ -1813,6 +1869,14 @@

4. Latest articles on Neural ODEs

0 + + SMURF: Continuous Dynamics for Motion-Deblurring Radiance Fields + Jungho Lee, Dogyoon Lee, Minhyeok Lee, Donghyung Kim, Sangyoun Lee + 2024-03-12 + ArXiv + 0 + + Development and Implementation of Physics-Informed Neural ODE for Dynamics Modeling of a Fixed-Wing Aircraft Under Icing/Fault Jinyi Ma, Yiyang Li, Jingqi Tu, Yiming Zhang, J. Ai, Yiqun Dong @@ -1821,6 +1885,62 @@

4. Latest articles on Neural ODEs

0 + + Multi-conditioned Graph Diffusion for Neural Architecture Search + Rohan Asthana, Joschua Conrad, Youssef Dawoud, Maurits Ortmanns, Vasileios Belagiannis + 2024-03-09 + ArXiv + 0 + + + + A Two-Stage Training Method for Modeling Constrained Systems With Neural Networks + C. Coelho, M. F. P. Costa, L. L. Ferr'as + 2024-03-05 + ArXiv + 0 + + + + Neural Fractional Differential Equations + C. Coelho, M. F. P. Costa, L. L. Ferr'as + 2024-03-05 + ArXiv + 0 + + + + Dynamic Gaussian Graph Operator: Learning parametric partial differential equations in arbitrary discrete mechanics problems + Chu Wang, Jinhong Wu, Yanzhi Wang, Zhijian Zha, Qi Zhou + 2024-03-05 + ArXiv + 0 + + + + Physics-Informed Neural Networks with Skip Connections for Modeling and Control of Gas-Lifted Oil Wells + Jonas Ekeland Kittelsen, Eric A. Antonelo, E. Camponogara, Lars Struen Imsland + 2024-03-04 + ArXiv + 0 + + + + Neural Graph Generator: Feature-Conditioned Graph Generation using Latent Diffusion Models + Iakovos Evdaimon, Giannis Nikolentzos, Michail Chatzianastasis, Hadi Abdine, M. Vazirgiannis + 2024-03-03 + ArXiv + 0 + + + + Representation Learning on Heterophilic Graph with Directional Neighborhood Attention + Qincheng Lu, Jiaqi Zhu, Sitao Luan, Xiaomeng Chang + 2024-03-03 + ArXiv + 0 + + Continuous Image Outpainting with Neural ODE Penglei Gao, Xi Yang, Rui Zhang, Kaizhu Huang @@ -1831,12 +1951,20 @@

4. Latest articles on Neural ODEs

Probabilistic locked mode predictor in the presence of a resistive wall and finite island saturation in tokamaks - C. Akçay, John M. Finn, Dylan P. Brennan, K. E. J. Olofsson, A. J. Cole + C. Akçay, J. M. Finn, Dylan P. Brennan, K. E. J. Olofsson, A. J. Cole 2024-03-01 Physics of Plasmas 0 + + RNA Velocity Prediction via Neural Ordinary Differential Equation + Chenxi Xie, Yueyuxiao Yang, Hao Yu, Qiushun He, Mingze Yuan, Bin Dong, Li Zhang, Mengcheng Yang + 2024-03-01 + iScience + 0 + + A hybrid neural ordinary differential equation model of the cardiovascular system Gevik Grigorian, Sandip V. George, Sam Lishak, Rebecca J. Shipley, S. Arridge @@ -1845,6 +1973,22 @@

4. Latest articles on Neural ODEs

0 + + Nonlinear Sheaf Diffusion in Graph Neural Networks + Olga Zaghen + 2024-03-01 + ArXiv + 0 + + + + Causal Graph ODE: Continuous Treatment Effect Modeling in Multi-agent Dynamical Systems + Zijie Huang, Jeehyun Hwang, Junkai Zhang, Jinwoo Baik, Weitong Zhang, Dominik Wodarz, Yizhou Sun, Q. Gu, Wei Wang + 2024-02-29 + ArXiv + 0 + + DiffAssemble: A Unified Graph-Diffusion Model for 2D and 3D Reassembly Gianluca Scarpellini, Stefano Fiorini, Francesco Giuliari, Pietro Morerio, A. D. Bue @@ -1874,7 +2018,7 @@

4. Latest articles on Neural ODEs

Benjamin Walker, Andrew D. McLeod, Tiexin Qin, Yichuan Cheng, Haoliang Li, Terry Lyons 2024-02-28 ArXiv - 0 + 1 @@ -2205,6 +2349,14 @@

4. Latest articles on Neural ODEs

0 + + A Deep Learning Model of Amyloid-${\boldsymbol{\beta }}$ Diffusion Simulation + Byeongchang Jeong, Daegyeom Kim, Hyun-Ghang Jeong, Cheol E. Han + 2024-01-28 + 2024 International Conference on Electronics, Information, and Communication (ICEIC) + 0 + + Continuously Evolving Graph Neural Controlled Differential Equations for Traffic Forecasting Jiajia Wu, Ling Chen @@ -2234,7 +2386,7 @@

4. Latest articles on Neural ODEs

Mart'in Sevilla, Antonio G. Marques, Santiago Segarra 2024-01-25 ArXiv - 0 + 1 @@ -2397,158 +2549,6 @@

4. Latest articles on Neural ODEs

0 - - Inverse Nonlinearity Compensation of Hyperelastic Deformation in Dielectric Elastomer for Acoustic Actuation - J. Lee, G. An, Jeong-Yun Sun, Kyogu Lee - 2024-01-08 - ArXiv - 0 - - - - PosDiffNet: Positional Neural Diffusion for Point Cloud Registration in a Large Field of View with Perturbations - Rui She, Sijie Wang, Qiyu Kang, Kai Zhao, Yang Song, Wee Peng Tay, Tianyu Geng, Xingchao Jian - 2024-01-06 - ArXiv - 0 - - - - A Bidirectional Feedforward Neural Network Architecture Using the Discretized Neural Memory Ordinary Differential Equation - Hao Niu, Zhang Yi, Tao He - 2024-01-05 - International journal of neural systems - 0 - - - - Geometric-Facilitated Denoising Diffusion Model for 3D Molecule Generation - Can Xu, Haosen Wang, Weigang Wang, Pengfei Zheng, Hongyang Chen - 2024-01-05 - AAAI Conference on Artificial Intelligence - 1 - - - - Multi-relational Graph Diffusion Neural Network with Parallel Retention for Stock Trends Classification - Zinuo You, Pengju Zhang, Jin Zheng, John Cartlidge - 2024-01-05 - ArXiv - 0 - - - - A Cost-Efficient FPGA Implementation of Tiny Transformer Model using Neural ODE - Ikumi Okubo, Keisuke Sugiura, Hiroki Matsutani - 2024-01-05 - ArXiv - 1 - - - - Physics-Informed Neural Networks for High-Frequency and Multi-Scale Problems using Transfer Learning - Abdul Hannan Mustajab, Hao Lyu, Z. Rizvi, Frank Wuttke - 2024-01-05 - ArXiv - 0 - - - - Neural ordinary differential grey algorithm to forecasting MEVW systems - Z. Chen, Y. Meng, Ruei-Yuan Wang, Timothy Chen - 2024-01-04 - Int. J. Comput. Commun. Control - 0 - - - - Information Cascade Prediction of complex networks based on Physics-informed Graph Convolutional Network - Dingguo Yu, Yijie Zhou, Suiyu Zhang, Wenbing Li, Michael Small, Ke-ke Shang - 2024-01-04 - New Journal of Physics - 0 - - - - Gain Scheduling with a Neural Operator for a Transport PDE with Nonlinear Recirculation - Maxence Lamarque, Luke Bhan, R. Vázquez, Miroslav Krstic - 2024-01-04 - ArXiv - 1 - - - - DGDNN: Decoupled Graph Diffusion Neural Network for Stock Movement Prediction - Zinuo You, Zijian Shi, Hongbo Bo, John Cartlidge, Li Zhang, Yan Ge - 2024-01-03 - ArXiv - 1 - - - - Dynamics of a random Hopfield neural lattice model with adaptive synapses and delayed Hebbian learning - Xiaoying Han, P. Kloeden - 2024-01-02 - Ukrains’kyi Matematychnyi Zhurnal - 0 - - - - Solving multiscale dynamical systems by deep learning - Z. Xu, Junjie Yao, Yuxiao Yi, Liangkai Hang, E. Weinan, Yaoyu Zhang, Tianhan Zhang - 2024-01-02 - ArXiv - 1 - - - - nmODE-Unet: A Novel Network for Semantic Segmentation of Medical Images - Shubin Wang, Yuanyuan Chen, Zhang Yi - 2024-01-02 - Applied Sciences - 0 - - - - Deep learning bulk spacetime from boundary optical conductivity - Byoungjoon Ahn, Hyun-Sik Jeong, Keun-Young Kim, Kwan Yun - 2024-01-01 - Journal of High Energy Physics - 2 - - - - ML-Based Spectral Power Profiles Prediction in Presence of ISRS for Ultra-Wideband Transmission - A. M. Rosa Brusin, A. Nespola, M. R. Zefreh, S. Piciaccia, P. Poggiolini, F. Forghieri, A. Carena - 2024-01-01 - Journal of Lightwave Technology - 0 - - - - Numerical analysis of thermophoretic particle deposition on 3D Casson nanofluid: Artificial neural networks-based Levenberg–Marquardt algorithm - Amna Khan, Fahad Aljuaydi, Zeeshan Khan, Saeed Islam - 2024-01-01 - Open Physics - 0 - - - - Physics-Informed Neural Networks for 2nd order ODEs with sharp gradients - Mario De Florio, E. Schiassi, F. Calabrò, R. Furfaro - 2024-01-01 - J. Comput. Appl. Math. - 7 - - - - Variational Bayesian Learning With Reliable Likelihood Approximation for Accurate Process Quality Evaluation - Shilong Wang, Yu Wang, Bo Yang, Fan Mo, Zhengping Zhang - 2024-01-01 - IEEE Transactions on Industrial Informatics - 1 - -

@@ -2558,14 +2558,14 @@

4. Latest articles on Neural ODEs

Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations M. Raissi, P. Perdikaris, G. Karniadakis 2019-02-01 J. Comput. Phys. - 6364 + 6409 Hidden fluid mechanics: Learning velocity and pressure fields from flow visualizations M. Raissi, A. Yazdani, G. Karniadakis 2020-01-30 Science - 1039 + 1048 DeepXDE: A Deep Learning Library for Solving Differential Equations Lu Lu, Xuhui Meng, Zhiping Mao, G. Karniadakis 2019-07-10 ArXiv - 993 + 995 Physics Informed Deep Learning (Part I): Data-driven Solutions of Nonlinear Partial Differential Equations M. Raissi, P. Perdikaris, G. Karniadakis 2017-11-28 ArXiv - 700 + 703 NSFnets (Navier-Stokes flow nets): Physics-informed neural networks for the incompressible Navier-Stokes equations Xiaowei Jin, Shengze Cai, Hui Li, G. Karniadakis 2020-03-13 J. Comput. Phys. - 538 + 542 Physics Informed Deep Learning (Part II): Data-driven Discovery of Nonlinear Partial Differential Equations M. Raissi, P. Perdikaris, G. Karniadakis 2017-11-28 ArXiv - 532 + 533 Physics-informed neural networks (PINNs) for fluid mechanics: a review Shengze Cai, Zhiping Mao, Zhicheng Wang, Minglang Yin, G. Karniadakis 2021-05-20 Acta Mechanica Sinica - 525 + 532 B-PINNs: Bayesian Physics-Informed Neural Networks for Forward and Inverse PDE Problems with Noisy Data Liu Yang, Xuhui Meng, G. Karniadakis 2020-03-13 ArXiv - 508 + 515 Scientific Machine Learning Through Physics–Informed Neural Networks: Where we are and What’s Next S. Cuomo, Vincenzo Schiano Di Cola, F. Giampaolo, G. Rozza, Maizar Raissi, F. Piccialli 2022-01-14 Journal of Scientific Computing - 503 + 509 Adaptive activation functions accelerate convergence in deep and physics-informed neural networks Ameya Dilip Jagtap, G. Karniadakis 2019-06-04 J. Comput. Phys. - 496 + 498 Universal Differential Equations for Scientific Machine Learning Christopher Rackauckas, Yingbo Ma, Julius Martensen, Collin Warner, K. Zubov, R. Supekar, Dominic J. Skinner, A. Ramadhan 2020-01-13 ArXiv - 444 + 448 fPINNs: Fractional Physics-Informed Neural Networks G. Pang, Lu Lu, G. Karniadakis 2018-11-20 SIAM J. Sci. Comput. - 444 + 445 Transfer learning enhanced physics informed neural network for phase-field modeling of fracture S. Goswami, C. Anitescu, S. Chakraborty, T. Rabczuk 2019-07-04 ArXiv - 372 + 375 Extended Physics-informed Neural Networks (XPINNs): A Generalized Space-Time Domain Decomposition based Deep Learning Framework for Nonlinear Partial Differential Equations Ameya Dilip Jagtap, G. Karniadakis 2020-06-01 Communications in Computational Physics - 360 + 361 Characterizing possible failure modes in physics-informed neural networks A. Krishnapriyan, A. Gholami, Shandian Zhe, Robert M. Kirby, Michael W. Mahoney 2021-09-02 Neural Information Processing Systems - 348 + 351 Understanding and Mitigating Gradient Flow Pathologies in Physics-Informed Neural Networks Sifan Wang, Yujun Teng, P. Perdikaris 2021-01-01 SIAM J. Sci. Comput. - 337 + 342 hp-VPINNs: Variational Physics-Informed Neural Networks With Domain Decomposition E. Kharazmi, Zhongqiang Zhang, G. Karniadakis 2020-03-11 ArXiv - 314 + 318 @@ -831,57 +831,57 @@

3. Most cited articles on PINNs

Quantifying total uncertainty in physics-informed neural networks for solving forward and inverse stochastic problems Dongkun Zhang, Lu Lu, Ling Guo, G. Karniadakis 2018-09-21 J. Comput. Phys. - 304 + 306 Adversarial Uncertainty Quantification in Physics-Informed Neural Networks Yibo Yang, P. Perdikaris 2018-11-09 ArXiv - 288 + 290 PPINN: Parareal Physics-Informed Neural Network for time-dependent PDEs Xuhui Meng, Zhen Li, Dongkun Zhang, G. Karniadakis 2019-09-23 ArXiv - 285 + 287 Towards Physics-informed Deep Learning for Turbulent Flow Prediction Rui Wang, K. Kashinath, M. Mustafa, A. Albert, Rose Yu 2019-11-20 Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining - 272 + 274 Physics-informed neural networks with hard constraints for inverse design Lu Lu, R. Pestourie, Wenjie Yao, Zhicheng Wang, F. Verdugo, Steven G. Johnson 2021-01-01 ArXiv - 265 + 266 @@ -897,90 +897,90 @@

3. Most cited articles on PINNs

Understanding and mitigating gradient pathologies in physics-informed neural networks Sifan Wang, Yujun Teng, P. Perdikaris 2020-01-13 ArXiv - 257 + 259 On the eigenvector bias of Fourier feature networks: From regression to solving multi-scale PDEs with physics-informed neural networks Sifan Wang, Hanwen Wang, P. Perdikaris 2020-12-18 ArXiv - 244 + 245 Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems Jeremy Yu, Lu Lu, Xuhui Meng, G. Karniadakis 2021-11-01 ArXiv - 226 + 228 Self-Adaptive Physics-Informed Neural Networks using a Soft Attention Mechanism L. McClenny, U. Braga-Neto 2020-09-07 J. Comput. Phys. - 222 + 224 Physics-informed learning of governing equations from scarce data Zhao Chen, Yang Liu, Hao Sun 2020-05-05 Nature Communications - 181 + 184 Machine learning for metal additive manufacturing: predicting temperature and melt pool fluid dynamics using physics-informed neural networks Qiming Zhu, Zeliang Liu, Jinhui Yan 2020-07-28 Computational Mechanics - 179 + 183 Physics-Informed Neural Operator for Learning Partial Differential Equations Zong-Yi Li, Hongkai Zheng, Nikola B. Kovachki, David Jin, Haoxuan Chen, Burigede Liu, K. Azizzadenesheli, Anima Anandkumar 2021-11-06 ArXiv - 175 + 179 Physics-Informed Neural Networks for Multiphysics Data Assimilation with Application to Subsurface Transport Qizhi He, D. Barajas-Solano, G. Tartakovsky, A. Tartakovsky 2019-12-06 ArXiv - 171 + 172 @@ -1018,57 +1018,57 @@

3. Most cited articles on PINNs

- Physics-Informed Neural Network for Ultrasound Nondestructive Quantification of Surface Breaking Cracks - K. Shukla, P. C. D. Leoni, J. Blackshire, D. Sparkman, G. Karniadakis - 2020-05-07 - Journal of Nondestructive Evaluation - 152 + Physics-informed deep learning for incompressible laminar flows + Chengping Rao, Hao Sun, Yang Liu + 2020-02-24 + ArXiv + 153 - Physics-informed deep learning for incompressible laminar flows - Chengping Rao, Hao Sun, Yang Liu - 2020-02-24 - ArXiv - 149 + Physics-Informed Neural Network for Ultrasound Nondestructive Quantification of Surface Breaking Cracks + K. Shukla, P. C. D. Leoni, J. Blackshire, D. Sparkman, G. Karniadakis + 2020-05-07 + Journal of Nondestructive Evaluation + 153 Physics informed deep learning for computational elastodynamics without labeled data Chengping Rao, Hao Sun, Yang Liu 2020-06-10 ArXiv - 147 + 148 Hidden Fluid Mechanics: A Navier-Stokes Informed Deep Learning Framework for Assimilating Flow Visualization Data M. Raissi, A. Yazdani, G. Karniadakis 2018-08-13 ArXiv - 142 + 143 A comprehensive study of non-adaptive and residual-based adaptive sampling for physics-informed neural networks Chen-Chun Wu, M. Zhu, Qinyan Tan, Yadhu Kartha, Lu Lu 2022-07-21 ArXiv - 139 + 140 @@ -1084,24 +1084,24 @@

3. Most cited articles on PINNs

A fast and accurate physics-informed neural network reduced order model with shallow masked autoencoder Youngkyu Kim, Youngsoo Choi, D. Widemann, T. Zohdi 2020-09-25 ArXiv - 132 + 133 Respecting causality is all you need for training physics-informed neural networks Sifan Wang, Shyam Sankaran, P. Perdikaris 2022-03-14 ArXiv - 130 + 132 @@ -1148,6 +1148,17 @@

3. Most cited articles on PINNs

121 + + + Physics-informed neural networks for solving Reynolds-averaged Navier-Stokes equations + Hamidreza Eivazi, M. Tahani, P. Schlatter, R. Vinuesa + 2021-07-22 + ArXiv + 120 + + Three ways to solve partial differential equations with neural networks — A review J. Blechschmidt, O. Ernst 2021-02-23 GAMM‐Mitteilungen - 118 + 119 - Physics-informed neural networks for solving Reynolds-averaged Navier-Stokes equations - Hamidreza Eivazi, M. Tahani, P. Schlatter, R. Vinuesa - 2021-07-22 - ArXiv + The Old and the New: Can Physics-Informed Deep-Learning Replace Traditional Linear Solvers? + S. Markidis + 2021-03-12 + Frontiers in Big Data 117 - The Old and the New: Can Physics-Informed Deep-Learning Replace Traditional Linear Solvers? - S. Markidis - 2021-03-12 - Frontiers in Big Data - 116 + Analyses of internal structures and defects in materials using physics-informed neural networks + Enrui Zhang, M. Dao, G. Karniadakis, S. Suresh + 2022-02-01 + Science Advances + 114 @@ -1206,34 +1217,23 @@

3. Most cited articles on PINNs

- Analyses of internal structures and defects in materials using physics-informed neural networks - Enrui Zhang, M. Dao, G. Karniadakis, S. Suresh - 2022-02-01 - Science Advances - 112 - - - - nPINNs: nonlocal Physics-Informed Neural Networks for a parametrized nonlocal universal Laplacian operator. Algorithms and Applications G. Pang, M. D'Elia, M. Parks, G. Karniadakis 2020-04-01 ArXiv - 110 + 112 Physics-informed neural networks for inverse problems in supersonic flows Ameya Dilip Jagtap, Zhiping Mao, N. Adams, G. Karniadakis 2022-02-23 J. Comput. Phys. - 108 + 110 @@ -1249,45 +1249,45 @@

3. Most cited articles on PINNs

- CAN-PINN: A Fast Physics-Informed Neural Network Based on Coupled-Automatic-Numerical Differentiation Method - P. Chiu, Jian Cheng Wong, C. Ooi, M. Dao, Y. Ong - 2021-10-29 - ArXiv - 96 - - - - A survey on deep learning tools dealing with data scarcity: definitions, challenges, solutions, tips, and applications Laith Alzubaidi, Jinshuai Bai, Aiman Al-Sabaawi, José I. Santamaría, A. Albahri, B. S. Al-dabbagh, M. Fadhel, M. Manoufali, Jinglan Zhang, Ali H. Al-timemy, Ye Duan, Amjed Abdullah, Laith Farhan, Yi Lu, Ashish Gupta, Felix Albu, Amin Abbosh, Yuantong Gu 2023-04-14 Journal of Big Data - 96 + 100 - Locally adaptive activation functions with slope recovery term for deep and physics-informed neural networks - Ameya Dilip Jagtap, Kenji Kawaguchi, G. Karniadakis - 2019-09-25 + CAN-PINN: A Fast Physics-Informed Neural Network Based on Coupled-Automatic-Numerical Differentiation Method + P. Chiu, Jian Cheng Wong, C. Ooi, M. Dao, Y. Ong + 2021-10-29 ArXiv - 94 + 97 A physics-informed deep learning approach for bearing fault detection Sheng Shen, Hao Lu, Mohammadkazem Sadoughi, Chao Hu, V. Nemani, Adam Thelen, Keith Webster, M. Darr, Jeff Sidon, S. Kenny 2021-08-01 Eng. Appl. Artif. Intell. + 95 + + + + + Locally adaptive activation functions with slope recovery term for deep and physics-informed neural networks + Ameya Dilip Jagtap, Kenji Kawaguchi, G. Karniadakis + 2019-09-25 + ArXiv 94 @@ -1337,13 +1337,13 @@

3. Most cited articles on PINNs

Physics-Informed Deep Learning for Musculoskeletal Modeling: Predicting Muscle Forces and Joint Kinematics From Surface EMG Jie Zhang, Yihui Zhao, Fergus Shone, Zhenhong Li, Alejandro F Frangi, Shengquan Xie, Zhi-Li Zhang 2022-07-04 IEEE Transactions on Neural Systems and Rehabilitation Engineering - 85 + 87 @@ -1370,68 +1370,68 @@

3. Most cited articles on PINNs

The Neural Particle Method - An Updated Lagrangian Physics Informed Neural Network for Computational Fluid Dynamics H. Wessels, C. Weißenfels, P. Wriggers 2020-03-18 ArXiv - 78 + 79 Thermodynamically consistent physics-informed neural networks for hyperbolic systems Ravi G. Patel, Indu Manickam, N. Trask, M. Wood, Myoungkyu Lee, I. Tomas, E. Cyr 2020-12-09 J. Comput. Phys. - 78 + 79 - PINNeik: Eikonal solution using physics-informed neural networks - U. Waheed, E. Haghighat, T. Alkhalifah, Chao Song, Q. Hao - 2020-07-16 - Comput. Geosci. - 76 + A nonlocal physics-informed deep learning framework using the peridynamic differential operator + E. Haghighat, A. Bekar, E. Madenci, R. Juanes + 2020-05-31 + ArXiv + 77 Physics Informed Neural Networks for Simulating Radiative Transfer Siddhartha Mishra, R. Molinaro 2020-09-25 ArXiv - 75 + 76 - A nonlocal physics-informed deep learning framework using the peridynamic differential operator - E. Haghighat, A. Bekar, E. Madenci, R. Juanes - 2020-05-31 - ArXiv - 74 + PINNeik: Eikonal solution using physics-informed neural networks + U. Waheed, E. Haghighat, T. Alkhalifah, Chao Song, Q. Hao + 2020-07-16 + Comput. Geosci. + 76 Physics informed neural networks for continuum micromechanics Alexander Henkes, H. Wessels, R. Mahnken 2021-10-14 PAMM - 74 + 75 @@ -1447,13 +1447,13 @@

3. Most cited articles on PINNs

A Physics-Informed Deep Learning Paradigm for Car-Following Models Zhaobin Mo, Xuan Di, Rongye Shi 2020-12-24 ArXiv - 71 + 73 @@ -1480,35 +1480,35 @@

3. Most cited articles on PINNs

- A High-Efficient Hybrid Physics-Informed Neural Networks Based on Convolutional Neural Network - Z. Fang - 2021-04-13 - IEEE Transactions on Neural Networks and Learning Systems - 68 + Biologically-informed neural networks guide mechanistic modeling from sparse experimental data + John H. Lagergren, John T. Nardini, R. Baker, M. Simpson, K. Flores + 2020-05-26 + PLoS Computational Biology + 70 - Biologically-informed neural networks guide mechanistic modeling from sparse experimental data - John H. Lagergren, John T. Nardini, R. Baker, M. Simpson, K. Flores - 2020-05-26 - PLoS Computational Biology + A High-Efficient Hybrid Physics-Informed Neural Networks Based on Convolutional Neural Network + Z. Fang + 2021-04-13 + IEEE Transactions on Neural Networks and Learning Systems 68 A two-stage physics-informed neural network method based on conserved quantities and applications in localized wave solutions Shuning Lin, Yong Chen 2021-07-02 J. Comput. Phys. - 66 + 67 @@ -1581,22 +1581,22 @@

3. Most cited articles on PINNs

- Modeling System Dynamics with Physics-Informed Neural Networks Based on Lagrangian Mechanics - Manuel A. Roehrl, T. Runkler, Veronika Brandtstetter, Michel Tokic, Stefan Obermayer - 2020-05-29 + Error estimates of residual minimization using neural networks for linear PDEs + Yeonjong Shin, Zhongqiang Zhang, G. Karniadakis + 2020-10-15 ArXiv 60 - Error estimates of residual minimization using neural networks for linear PDEs - Yeonjong Shin, Zhongqiang Zhang, G. Karniadakis - 2020-10-15 + Modeling System Dynamics with Physics-Informed Neural Networks Based on Lagrangian Mechanics + Manuel A. Roehrl, T. Runkler, Veronika Brandtstetter, Michel Tokic, Stefan Obermayer + 2020-05-29 ArXiv - 59 + 60 @@ -1645,13 +1645,13 @@

3. Most cited articles on PINNs

A Physics-Informed Deep Learning Paradigm for Traffic State and Fundamental Diagram Estimation Rongye Shi, Zhaobin Mo, Kuang Huang, Xuan Di, Qi Du 2021-06-06 IEEE Transactions on Intelligent Transportation Systems - 56 + 55 @@ -1680,31 +1680,31 @@

3. Most cited articles on PINNs

- Bayesian Physics-Informed Neural Networks for real-world nonlinear dynamical systems - K. Linka, Amelie Schäfer, Xuhui Meng, Zongren Zou, G. Karniadakis, E. Kuhl - 2022-05-12 + A mixed formulation for physics-informed neural networks as a potential solver for engineering problems in heterogeneous domains: comparison with finite element method + Shahed Rezaei, A. Harandi, Ahmad Moeineddin, Bai-Xiang Xu, S. Reese + 2022-06-27 ArXiv 52 - Robust Training and Initialization of Deep Neural Networks: An Adaptive Basis Viewpoint - E. Cyr, Mamikon A. Gulian, Ravi G. Patel, M. Perego, N. Trask - 2019-12-10 + Bayesian Physics-Informed Neural Networks for real-world nonlinear dynamical systems + K. Linka, Amelie Schäfer, Xuhui Meng, Zongren Zou, G. Karniadakis, E. Kuhl + 2022-05-12 ArXiv - 51 + 52 - A mixed formulation for physics-informed neural networks as a potential solver for engineering problems in heterogeneous domains: comparison with finite element method - Shahed Rezaei, A. Harandi, Ahmad Moeineddin, Bai-Xiang Xu, S. Reese - 2022-06-27 + Robust Training and Initialization of Deep Neural Networks: An Adaptive Basis Viewpoint + E. Cyr, Mamikon A. Gulian, Ravi G. Patel, M. Perego, N. Trask + 2019-12-10 ArXiv 51 @@ -1724,10 +1724,10 @@

3. Most cited articles on PINNs

- Physics-informed neural network simulation of multiphase poroelasticity using stress-split sequential training - E. Haghighat, Daniel Amini, R. Juanes - 2021-10-06 - ArXiv + Error analysis for physics-informed neural networks (PINNs) approximating Kolmogorov PDEs + Tim De Ryck, Siddhartha Mishra + 2021-06-28 + Advances in Computational Mathematics 51 @@ -1749,6 +1749,14 @@

4. Latest articles on PINNs

+ + Interface crack analysis in 2D bounded dissimilar materials using an enriched physics-informed neural networks + Yan Gu, Longtao Xie, Wenzhen Qu, Shengdong Zhao + 2024-06-01 + Engineering Analysis with Boundary Elements + 0 + + Inverse physics–informed neural networks for digital twin–based bearing fault diagnosis under imbalanced samples Yi Qin, Hongyu Liu, Yi Wang, Yongfang Mao @@ -1781,6 +1789,46 @@

4. Latest articles on PINNs

0 + + A physics‐informed machine learning prediction for thermal analysis in a convective‐radiative concave fin with periodic boundary conditions + Chandan Kumar, P. Srilatha, K. Karthik, Channaiah Somashekar, Kallur Venkat Nagaraja, R. S. Varun Kumar, Nehad Ali Shah + 2024-04-04 + ZAMM - Journal of Applied Mathematics and Mechanics / Zeitschrift für Angewandte Mathematik und Mechanik + 0 + + + + A Data Assimilation Methodology to Analyze the Unsaturated Seepage of an Earth–Rockfill Dam Using Physics-Informed Neural Networks Based on Hybrid Constraints + Qianwei Dai, Wei Zhou, Run‐Ying He, Junsheng Yang, Bin Zhang, Yi Lei + 2024-04-04 + Water + 0 + + + + Inverse design of electromagnetic metamaterials: From iterative to deep learning-based methods + Chen Ma, Zhenyu Wang, Hui Zhang, Fengyuan Yang, Jianlin Chen, Qinghua Ren, Yiming Ma, Nan Wang + 2024-04-04 + Journal of Micromechanics and Microengineering + 0 + + + + Physics-informed deep learning to quantify anomalies for real-time fault mitigation in 3D printing + Benjamin Uhrich, Nils Pfeifer, Martin Schäfer, O. Theile, Erhard Rahm + 2024-04-03 + Applied Intelligence + 0 + + + + Overview of the Application of Physically Informed Neural Networks to the Problems of Nonlinear Fluid Flow in Porous Media + Nina Dieva, Damir Aminev, Marina Kravchenko, Nikolay Smirnov + 2024-04-02 + Computation + 0 + + Reconstructing unsaturated infiltration behavior with sparse data via physics-informed deep learning Peng Lan, Jingjing Su, Shuairun Zhu, Jinsong Huang, Sheng Zhang @@ -1797,12 +1845,28 @@

4. Latest articles on PINNs

0 + + A PINN approach for identifying governing parameters of noisy thermoacoustic systems + Hwijae Son, Minwoo Lee + 2024-04-01 + Journal of Fluid Mechanics + 0 + + A hybrid model-data-driven framework for inverse load identification of interval structures based on physics-informed neural network and improved Kalman filter algorithm Yaru Liu, Lei Wang, Bing Feng Ng 2024-04-01 Applied Energy - 1 + 2 + + + + Physics-informed neural network-based magnetostriction model for grain-oriented electrical steels + Kaixing Hong, Jingchun Zhang, Jing Zheng, Suan Xu + 2024-04-01 + Journal of Magnetism and Magnetic Materials + 0 @@ -1823,7 +1887,7 @@

4. Latest articles on PINNs

Sequencing Initial Conditions in Physics-Informed Neural Networks - Saman Hooshyar, Arash Elahi + S. Hooshyar, Arash Elahi 2024-03-26 Journal of Chemistry and Environment 0 @@ -2005,6 +2069,38 @@

4. Latest articles on PINNs

0 + + Separable Physics-informed Neural Networks for Solving the BGK Model of the Boltzmann Equation + Jaemin Oh, Seung-Yeon Cho, Seok-Bae Yun, Eunbyung Park, Youngjoon Hong + 2024-03-10 + ArXiv + 0 + + + + A Model Hierarchy for Predicting the Flow in Stirred Tanks with Physics-Informed Neural Networks + Veronika Tr'avn'ikov'a, Daniel Wolff, Nico Dirkes, S. Elgeti, E. Lieres, Marek Behr + 2024-03-07 + ArXiv + 0 + + + + Uncertainty quantification for deeponets with ensemble kalman inversion + Andrew Pensoneault, Xueyu Zhu + 2024-03-06 + ArXiv + 0 + + + + TGPT-PINN: Nonlinear model reduction with transformed GPT-PINNs + Yanlai Chen, Yajie Ji, A. Narayan, Zhenli Xu + 2024-03-06 + ArXiv + 0 + + A Physics-Informed Neural Network model combined Pell–Lucas polynomials for solving the Lane–Emden type equation Zhoushun Zheng, Haolan Yuan, Jilong He @@ -2013,6 +2109,22 @@

4. Latest articles on PINNs

0 + + Physics-Informed Neural Networks with Skip Connections for Modeling and Control of Gas-Lifted Oil Wells + Jonas Ekeland Kittelsen, Eric A. Antonelo, E. Camponogara, Lars Struen Imsland + 2024-03-04 + ArXiv + 0 + + + + Macroscopic auxiliary asymptotic preserving neural networks for the linear radiative transfer equations + Hongyan Li, Song Jiang, Wenjun Sun, Liwei Xu, Guanyu Zhou + 2024-03-04 + ArXiv + 0 + + Residual-connected physics-informed neural network for anti-noise wind field reconstruction Runze Tian, Peng Kou, Yuanhang Zhang, Mingyang Mei, Zhihao Zhang, Deliang Liang @@ -2021,6 +2133,14 @@

4. Latest articles on PINNs

1 + + Accelerated Process Parameter Selection of Polymer-based Selective Laser Sintering via Hybrid Physics-informed Neural Network and Finite Element Surrogate Modelling + H. Yeh, Mohamad Bayat, Amirhossein Arzani, J. Hattel + 2024-03-01 + Applied Mathematical Modelling + 0 + + Predicting ocean pressure field with a physics-informed neural network. Seung-Jun Yoon, Yongsung Park, P. Gerstoft, Woojae Seong @@ -2095,7 +2215,7 @@

4. Latest articles on PINNs

Data-efficient surrogate modeling using meta-learning and physics-informed deep learning approaches - Youngjoon Jeong, Sang-ik Lee, Jong-hyuk Lee, Won Choi + Young-joon Jeong, Sang-ik Lee, Jong-hyuk Lee, Won Choi 2024-03-01 Expert Systems with Applications 0 @@ -2130,7 +2250,7 @@

4. Latest articles on PINNs

Longyan Wang, Meng Chen, Zhaohui Luo, Bowen Zhang, Jian Xu, Zilu Wang, A. C. Tan 2024-03-01 Energy - 0 + 1 @@ -2374,10 +2494,18 @@

4. Latest articles on PINNs

- Virtual draw of microstructured optical fiber based on physics-informed neural networks + Virtual draw of microstructured optical fiber based on physics-informed neural networks. Jinmin Ding, Chenyang Hou, Yiming Zhao, Hongwei Liu, Zixia Hu, Fanchao Meng, Sheng Liang 2024-02-16 - Optics Express + Optics express + 0 + + + + Exact Enforcement of Temporal Continuity in Sequential Physics-Informed Neural Networks + Pratanu Roy, Stephen T Castonguay + 2024-02-15 + ArXiv 0 @@ -2418,137 +2546,9 @@

4. Latest articles on PINNs

Dongjin Kim, Jaewook Lee 2024-02-13 Multiscale Science and Engineering - 0 - - - - Physics-informed neural networks to advance pavement engineering and management - Nima Kargah-Ostadi, K. Vasylevskyi, A. Ablets, A. Drach - 2024-02-13 - Road Materials and Pavement Design - 0 - - - - RBF-PINN: Non-Fourier Positional Embedding in Physics-Informed Neural Networks - Chengxi Zeng, T. Burghardt, A. Gambaruto - 2024-02-13 - ArXiv - 0 - - - - Approximating Families of Sharp Solutions to Fisher's Equation with Physics-Informed Neural Networks - Franz M. Rohrhofer, S. Posch, C. Gößnitzer, Bernhard C. Geiger - 2024-02-13 - ArXiv - 0 - - - - Score-Based Physics-Informed Neural Networks for High-Dimensional Fokker-Planck Equations - Zheyuan Hu, Zhongqiang Zhang, G. Karniadakis, Kenji Kawaguchi - 2024-02-12 - ArXiv - 2 - - - - Explicit Physics-Informed Deep Learning for Computer-Aided Diagnostic Tasks in Medical Imaging - Shira Nemirovsky-Rotman, Eyal Bercovich - 2024-02-12 - Machine Learning and Knowledge Extraction - 1 - - - - Physics-Informed Neural Networks with Hard Linear Equality Constraints - Hao Chen, Gonzalo E. Constante-Flores, Canzhou Li - 2024-02-11 - ArXiv - 0 - - - - Error Estimation for Physics-informed Neural Networks Approximating Semilinear Wave Equations - Beatrice Lorenz, Aras Bacho, Gitta Kutyniok - 2024-02-11 - ArXiv - 0 - - - - Training dynamics in Physics-Informed Neural Networks with feature mapping - Chengxi Zeng, T. Burghardt, A. Gambaruto - 2024-02-10 - ArXiv - 0 - - - - A Physics-Informed Neural Network for the Nonlinear Damage Identification in a Reinforced Concrete Bridge Pier Using Seismic Responses - Takahiro Yamaguchi, Tsukasa Mizutani - 2024-02-09 - Structural Control and Health Monitoring - 0 - - - - Optimization of Physics-Informed Neural Networks for Solving the Nolinear Schrödinger Equation - I. Chuprov, Jiexing Gao, D. Efremenko, E. Kazakov, F. Buzaev, V. Zemlyakov - 2024-02-09 - Doklady Mathematics - 0 - - - - Energy-based PINNs for solving coupled field problems: concepts and application to the optimal design of an induction heater - Marco Baldan, Paolo Di Barba - 2024-02-09 - ArXiv - 0 - - - - M‐PINN: A mesh‐based physics‐informed neural network for linear elastic problems in solid mechanics - Lu Wang, Guangyan Liu, Guanglun Wang, Kai Zhang - 2024-02-08 - International Journal for Numerical Methods in Engineering - 0 - - - - Neural functional a posteriori error estimates - V. Fanaskov, A. Rudikov, I. Oseledets - 2024-02-08 - ArXiv - 0 - - - - Insights into Multiscale Complexity: from Macroscopic Patterns to Microscopic Simulations via Deep Learning - Jing Wang, Zheng Li, Pengyu Lai, Rui Wang, Di Yang, Dewu Yang, Hui Xu - 2024-02-07 - ArXiv - 0 - - - - Densely Multiplied Physics Informed Neural Networks - Feilong Jiang, Xiaonan Hou, Min Xia - 2024-02-06 - ArXiv 1 - - The Challenges of the Nonlinear Regime for Physics-Informed Neural Networks - Andrea Bonfanti, Giuseppe Bruno, Cristina Cipriani - 2024-02-06 - ArXiv - 0 - -

@@ -2558,14 +2558,14 @@

4. Latest articles on PINNs

Learning to Simulate Complex Physics with Graph Networks Alvaro Sanchez-Gonzalez, Jonathan Godwin, T. Pfaff, Rex Ying, J. Leskovec, P. Battaglia 2020-02-21 ArXiv - 758 + 766 Whole-Genome Regression and Prediction Methods Applied to Plant and Animal Breeding G. de los Campos, J. Hickey, R. Pong-Wong, H. Daetwyler, M. Calus 2013-02-01 Genetics - 732 + 733 Learning Particle Dynamics for Manipulating Rigid Bodies, Deformable Objects, and Fluids Yunzhu Li, Jiajun Wu, Russ Tedrake, J. Tenenbaum, A. Torralba 2018-09-27 ArXiv - 289 + 292 @@ -677,24 +677,24 @@

3. Most cited articles on Physics-informed GNNs

Learning how to Active Learn: A Deep Reinforcement Learning Approach Meng Fang, Yuan Li, Trevor Cohn 2017-08-01 ArXiv - 240 + 244 Hamiltonian Graph Networks with ODE Integrators Alvaro Sanchez-Gonzalez, V. Bapst, Kyle Cranmer, P. Battaglia 2019-09-27 ArXiv - 153 + 154 @@ -787,13 +787,13 @@

3. Most cited articles on Physics-informed GNNs

Self-Imitation Learning by Planning Junhyuk Oh, Yijie Guo, Satinder Singh, Honglak Lee 2021-03-25 2021 IEEE International Conference on Robotics and Automation (ICRA) - 93 + 92 @@ -809,24 +809,24 @@

3. Most cited articles on Physics-informed GNNs

TANKBind: Trigonometry-Aware Neural NetworKs for Drug-Protein Binding Structure Prediction Wei Lu, Qifeng Wu, Jixian Zhang, Jiahua Rao, Chengtao Li, Shuangjia Zheng 2022-10-25 bioRxiv - 73 + 76 Human factors in resuscitation: Lessons learned from simulator studies Sabrina Hunziker, F. Tschan, N. Semmer, Michael D. Howell, Stephan Marsch 2010-10-01 Journal of Emergencies, Trauma and Shock - 70 + 69 @@ -928,6 +928,17 @@

3. Most cited articles on Physics-informed GNNs

54 + + + Distance-Weighted Graph Neural Networks on FPGAs for Real-Time Particle Reconstruction in High Energy Physics + Y. Iiyama, G. Cerminara, Abhijay Gupta, J. Kieseler, V. Loncar, M. Pierini, S. Qasim, M. Rieger, S. Summers, G. Onsem, K. Wozniak, J. Ngadiuba, G. D. Guglielmo, Javier Mauricio Duarte, P. Harris, D. Rankin, S. Jindariani, Miaoyuan Liu, K. Pedro, N. Tran, E. Kreinar, Zhenbin Wu + 2020-08-08 + Frontiers in Big Data + 53 + + - Distance-Weighted Graph Neural Networks on FPGAs for Real-Time Particle Reconstruction in High Energy Physics - Y. Iiyama, G. Cerminara, Abhijay Gupta, J. Kieseler, V. Loncar, M. Pierini, S. Qasim, M. Rieger, S. Summers, G. Onsem, K. Wozniak, J. Ngadiuba, G. D. Guglielmo, Javier Mauricio Duarte, P. Harris, D. Rankin, S. Jindariani, Miaoyuan Liu, K. Pedro, N. Tran, E. Kreinar, Zhenbin Wu - 2020-08-08 - Frontiers in Big Data - 52 - - - Retention of Skills After Simulation-based Training in Orthopaedic Surgery. - K. Atesok, R. Satava, Ann E. Van Heest, M. Hogan, R. Pedowitz, F. Fu, I. Sitnikov, Mn, J. Marsh, S. Hurwitz - 2016-08-01 - The Journal of the American Academy of Orthopaedic Surgeons + ForceNet: A Graph Neural Network for Large-Scale Quantum Calculations + Weihua Hu, Muhammed Shuaibi, Abhishek Das, Siddharth Goyal, Anuroop Sriram, J. Leskovec, Devi Parikh, C. L. Zitnick + 2021-03-02 + ArXiv 50 - ForceNet: A Graph Neural Network for Large-Scale Quantum Calculations - Weihua Hu, Muhammed Shuaibi, Abhishek Das, Siddharth Goyal, Anuroop Sriram, J. Leskovec, Devi Parikh, C. L. Zitnick - 2021-03-02 - ArXiv - 49 + Retention of Skills After Simulation-based Training in Orthopaedic Surgery. + K. Atesok, R. Satava, Ann E. Van Heest, M. Hogan, R. Pedowitz, F. Fu, I. Sitnikov, Mn, J. Marsh, S. Hurwitz + 2016-08-01 + The Journal of the American Academy of Orthopaedic Surgeons + 50 @@ -1075,22 +1075,22 @@

3. Most cited articles on Physics-informed GNNs

// alert (36) - Snapshot Hyperspectral Light Field Imaging - Zhiwei Xiong, Lizhi Wang, Huiqun Li, Dong Liu, Feng Wu - 2017-07-21 - 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) + A Deep Reinforcement Learning Technique for Vision-Based Autonomous Multirotor Landing on a Moving Platform + Alejandro Rodriguez-Ramos, Carlos Sampedro, Hriday Bavle, Ignacio Gil Moreno, P. Campoy + 2018-10-01 + 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 36 - A Deep Reinforcement Learning Technique for Vision-Based Autonomous Multirotor Landing on a Moving Platform - Alejandro Rodriguez-Ramos, Carlos Sampedro, Hriday Bavle, Ignacio Gil Moreno, P. Campoy - 2018-10-01 - 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) - 35 + Snapshot Hyperspectral Light Field Imaging + Zhiwei Xiong, Lizhi Wang, Huiqun Li, Dong Liu, Feng Wu + 2017-07-21 + 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) + 36 @@ -1106,13 +1106,13 @@

3. Most cited articles on Physics-informed GNNs

Graph Neural Networks as Gradient Flows Francesco Di Giovanni, J. Rowbottom, B. Chamberlain, Thomas Markovich, Michael M. Bronstein None ArXiv - 33 + 34 @@ -1137,6 +1137,17 @@

3. Most cited articles on Physics-informed GNNs

32 + + + Generative Tweening: Long-term Inbetweening of 3D Human Motions + Yi Zhou, Jingwan Lu, Connelly Barnes, Jimei Yang, Sitao Xiang, Hao Li + 2020-05-18 + ArXiv + 32 + + - Generative Tweening: Long-term Inbetweening of 3D Human Motions - Yi Zhou, Jingwan Lu, Connelly Barnes, Jimei Yang, Sitao Xiang, Hao Li - 2020-05-18 - ArXiv - 31 - - + Learned Simulators for Turbulence + Kimberly L. Stachenfeld, D. Fielding, Dmitrii Kochkov, M. Cranmer, T. Pfaff, Jonathan Godwin, Can Cui, S. Ho, P. Battaglia, Alvaro Sanchez-Gonzalez + None + International Conference on Learning Representations + 25 + + - Learned Simulators for Turbulence - Kimberly L. Stachenfeld, D. Fielding, Dmitrii Kochkov, M. Cranmer, T. Pfaff, Jonathan Godwin, Can Cui, S. Ho, P. Battaglia, Alvaro Sanchez-Gonzalez - None - International Conference on Learning Representations - 24 - - + Learning garment manipulation policies toward robot-assisted dressing + Fan Zhang, Y. Demiris + 2022-04-06 + Science Robotics + 22 + + - Learning garment manipulation policies toward robot-assisted dressing - Fan Zhang, Y. Demiris - 2022-04-06 - Science Robotics - 21 - - - M-ROSE: A Multi Robot Simulation Environment for Learning Cooperative Behavior - Sebastian Buck, M. Beetz, Thorsten Schmitt - None - International Symposium on Distributed Autonomous Robotic Systems - 17 - - + M-ROSE: A Multi Robot Simulation Environment for Learning Cooperative Behavior + Sebastian Buck, M. Beetz, Thorsten Schmitt + None + International Symposium on Distributed Autonomous Robotic Systems + 16 + + + TrafficBots: Towards World Models for Autonomous Driving Simulation and Motion Prediction + Zhejun Zhang, Alexander Liniger, Dengxin Dai, F. Yu, L. Gool + 2023-03-07 + 2023 IEEE International Conference on Robotics and Automation (ICRA) + 12 + + - TrafficBots: Towards World Models for Autonomous Driving Simulation and Motion Prediction - Zhejun Zhang, Alexander Liniger, Dengxin Dai, F. Yu, L. Gool - 2023-03-07 - 2023 IEEE International Conference on Robotics and Automation (ICRA) - 11 - - Symbolic Dynamic Programming for First-Order MDPs Craig Boutilier, R. Reiter, Bob Price 2001-08-04 International Joint Conference on Artificial Intelligence - 280 + 282 On Neural Differential Equations Patrick Kidger 2022-02-04 ArXiv - 133 + 134 @@ -906,23 +906,23 @@

3. Most cited articles on Symbolic regression

- The use of hypnosis with eating disorders. - M. Torem - None - Psychiatric medicine - 12 + Symbolic regression of multiple-time-scale dynamical systems + Theodore W. Cornforth, Hod Lipson + 2012-07-07 + Annual Conference on Genetic and Evolutionary Computation + 13 - Symbolic regression of multiple-time-scale dynamical systems - Theodore W. Cornforth, Hod Lipson - 2012-07-07 - Annual Conference on Genetic and Evolutionary Computation + The use of hypnosis with eating disorders. + M. Torem + None + Psychiatric medicine 12 @@ -1322,6 +1322,17 @@

3. Most cited articles on Symbolic regression

2 + + + Boolformer: Symbolic Regression of Logic Functions with Transformers + Stéphane d'Ascoli, Samy Bengio, Josh Susskind, Emmanuel Abb'e + 2023-09-21 + ArXiv + 2 + + - Boolformer: Symbolic Regression of Logic Functions with Transformers - Stéphane d'Ascoli, Samy Bengio, Josh Susskind, Emmanuel Abb'e - 2023-09-21 - ArXiv - 1 - -