Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations

20 January 2018

Papers citing "Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations"

50 / 146 papers shown

Title
A Sparse Bayesian Learning Algorithm for Estimation of Interaction Kernels in Motsch-Tadmor Model Jinchao Feng Sui Tang 26 0 0 11 May 2025
Predictive Digital Twins for Thermal Management Using Machine Learning and Reduced-Order Models Tamilselvan Subramani Sebastian Bartscher AI4CE 21 0 0 11 May 2025
Data-Efficient Kernel Methods for Learning Differential Equations and Their Solution Operators: Algorithms and Error Analysis Yasamin Jalalian Juan Felipe Osorio Ramirez Alexander W. Hsu Bamdad Hosseini H. Owhadi 48 0 0 02 Mar 2025
Neural Port-Hamiltonian Differential Algebraic Equations for Compositional Learning of Electrical Networks Cyrus Neary Nathan Tsao Ufuk Topcu 82 1 0 15 Dec 2024
PhyMPGN: Physics-encoded Message Passing Graph Network for spatiotemporal PDE systems Bocheng Zeng Qi Wang Ming Yan Yong-Jin Liu Ruizhi Chengze Yi Zhang Hongsheng Liu Zidong Wang Hao Sun AI4CE 44 3 0 02 Oct 2024
SetPINNs: Set-based Physics-informed Neural Networks Mayank Nagda Phil Ostheimer Thomas Specht Frank Rhein Fabian Jirasek Stephan Mandt Marius Kloft Sophie Fellenz 3DPC PINN 46 1 0 30 Sep 2024
Knowledge-data fusion oriented traffic state estimation: A stochastic physics-informed deep learning approach Ting Wang Ye Li Rongjun Cheng Guojian Zou Takao Dantsujic Dong Ngoduy 34 2 0 01 Sep 2024
Graph Neural Reaction Diffusion Models Moshe Eliasof Eldad Haber Eran Treister DiffM AI4CE 38 2 0 16 Jun 2024
RandONet: Shallow-Networks with Random Projections for learning linear and nonlinear operators Gianluca Fabiani Ioannis G. Kevrekidis Constantinos Siettos A. Yannacopoulos 27 11 0 08 Jun 2024
Polynomial-Augmented Neural Networks (PANNs) with Weak Orthogonality Constraints for Enhanced Function and PDE Approximation Madison Cooley Shandian Zhe Robert M. Kirby Varun Shankar 70 1 0 04 Jun 2024
Suppressing Modulation Instability with Reinforcement Learning Nikolay Kalmykov R. Zagidullin Oleg Y. Rogov Sergey Rykovanov Dmitry Dylov 21 0 0 05 Apr 2024
The Challenges of the Nonlinear Regime for Physics-Informed Neural Networks Andrea Bonfanti Giuseppe Bruno Cristina Cipriani 32 9 0 06 Feb 2024
Multi-Grade Deep Learning for Partial Differential Equations with Applications to the Burgers Equation Yuesheng Xu Taishan Zeng AI4CE 32 4 0 14 Sep 2023
Optimal Transport-inspired Deep Learning Framework for Slow-Decaying Kolmogorov n-width Problems: Exploiting Sinkhorn Loss and Wasserstein Kernel M. Khamlich F. Pichi G. Rozza 34 4 0 26 Aug 2023
Physics-Informed Machine Learning of Argon Gas-Driven Melt Pool Dynamics Rahul Sharma Y.B. Guo M. Raissi W. Guo PINN AI4CE 45 5 0 23 Jul 2023
Flow Map Learning for Unknown Dynamical Systems: Overview, Implementation, and Benchmarks V. Churchill D. Xiu AI4CE 28 10 0 20 Jul 2023
Koopman operator learning using invertible neural networks Yuhuang Meng Jian-Kai Huang Yue Qiu 13 12 0 30 Jun 2023
Meta-Learning for Airflow Simulations with Graph Neural Networks Wenzhuo Liu Mouadh Yagoubi Marc Schoenauer AI4CE 29 0 0 18 Jun 2023
PastNet: Introducing Physical Inductive Biases for Spatio-temporal Video Prediction Hao Wu Wei Xion Fan Xu Xian-Sheng Hua C. L. Philip Chen Xiansheng Hua AI4TS 39 27 0 19 May 2023
EPINN-NSE: Enhanced Physics-Informed Neural Networks for Solving Navier-Stokes Equations Ayoub Farkane Mounir Ghogho M. Oudani M. Boutayeb PINN 28 5 0 07 Apr 2023
GPT-PINN: Generative Pre-Trained Physics-Informed Neural Networks toward non-intrusive Meta-learning of parametric PDEs Yanlai Chen Shawn Koohy PINN AI4CE 37 24 0 27 Mar 2023
MetaPhysiCa: OOD Robustness in Physics-informed Machine Learning S Chandra Mouli M. A. Alam Bruno Ribeiro OOD 29 4 0 06 Mar 2023
Physics-Informed Deep Learning For Traffic State Estimation: A Survey and the Outlook Xuan Di Rongye Shi Zhaobin Mo Yongjie Fu PINN AI4TS AI4CE 32 28 0 03 Mar 2023
Ensemble learning for Physics Informed Neural Networks: a Gradient Boosting approach Zhiwei Fang Sizhuang He P. Perdikaris PINN AI4CE 16 5 0 25 Feb 2023
Discovering interpretable Lagrangian of dynamical systems from data Tapas Tripura S. Chakraborty 27 4 0 09 Feb 2023
Temporal Consistency Loss for Physics-Informed Neural Networks Sukirt Thakur M. Raissi H. Mitra A. Ardekani PINN 33 10 0 30 Jan 2023
Open Problems in Applied Deep Learning M. Raissi AI4CE 42 2 0 26 Jan 2023
Physics-Informed Neural Networks for Prognostics and Health Management of Lithium-Ion Batteries Pengfei Wen Z. Ye Yong Li Shaowei Chen Pu Xie Shuai Zhao 30 35 0 02 Jan 2023
PDE-LEARN: Using Deep Learning to Discover Partial Differential Equations from Noisy, Limited Data R. Stephany Christopher Earls 16 16 0 09 Dec 2022
Deep Learning Methods for Partial Differential Equations and Related Parameter Identification Problems Derick Nganyu Tanyu Jianfeng Ning Tom Freudenberg Nick Heilenkötter A. Rademacher U. Iben Peter Maass AI4CE 23 34 0 06 Dec 2022
Physics-Guided, Physics-Informed, and Physics-Encoded Neural Networks in Scientific Computing Salah A. Faroughi N. Pawar C. Fernandes Maziar Raissi Subasish Das N. Kalantari S. K. Mahjour PINN AI4CE 32 49 0 14 Nov 2022
SeismicNet: Physics-informed neural networks for seismic wave modeling in semi-infinite domain Pu Ren Chengping Rao Su Chen Jian-Xun Wang Hao Sun Yang Liu 44 41 0 25 Oct 2022
Learning governing physics from output only measurements Tapas Tripura S. Chakraborty 28 1 0 11 Aug 2022
Sparse Deep Neural Network for Nonlinear Partial Differential Equations Yuesheng Xu T. Zeng 33 5 0 27 Jul 2022
Tractable Dendritic RNNs for Reconstructing Nonlinear Dynamical Systems Manuela Brenner Florian Hess Jonas M. Mikhaeil Leonard Bereska Zahra Monfared Po-Chen Kuo Daniel Durstewitz AI4CE 42 30 0 06 Jul 2022
Noise-aware Physics-informed Machine Learning for Robust PDE Discovery Pongpisit Thanasutives Takeshi Morita M. Numao Ken-ichi Fukui PINN AI4CE 31 18 0 26 Jun 2022
Deep Learning of Chaotic Systems from Partially-Observed Data V. Churchill D. Xiu 40 12 0 12 May 2022
Wavelet neural operator: a neural operator for parametric partial differential equations Tapas Tripura S. Chakraborty 25 63 0 04 May 2022
Evaluating the Adversarial Robustness for Fourier Neural Operators Abolaji D. Adesoji Pin-Yu Chen AAML 30 1 0 08 Apr 2022
When Physics Meets Machine Learning: A Survey of Physics-Informed Machine Learning Chuizheng Meng Sungyong Seo Defu Cao Sam Griesemer Yan Liu PINN AI4CE 51 57 0 31 Mar 2022
On the Role of Fixed Points of Dynamical Systems in Training Physics-Informed Neural Networks Franz M. Rohrhofer S. Posch C. Gößnitzer Bernhard C. Geiger PINN 41 17 0 25 Mar 2022
Respecting causality is all you need for training physics-informed neural networks Sizhuang He Shyam Sankaran P. Perdikaris PINN CML AI4CE 49 199 0 14 Mar 2022
Robust Modeling of Unknown Dynamical Systems via Ensemble Averaged Learning V. Churchill Steve Manns Zhen Chen D. Xiu AI4CE 29 9 0 07 Mar 2022
Extension of Dynamic Mode Decomposition for dynamic systems with incomplete information based on t-model of optimal prediction Aleksandr Katrutsa S. Utyuzhnikov Ivan Oseledets 33 4 0 23 Feb 2022
Stochastic Modeling of Inhomogeneities in the Aortic Wall and Uncertainty Quantification using a Bayesian Encoder-Decoder Surrogate Sascha Ranftl Malte Rolf-Pissarczyk G. Wolkerstorfer Antonio Pepe Jan Egger W. Linden G. Holzapfel 31 9 0 21 Feb 2022
Modeling unknown dynamical systems with hidden parameters Xiaohan Fu Weize Mao L. Chang D. Xiu 24 5 0 03 Feb 2022
Constructing coarse-scale bifurcation diagrams from spatio-temporal observations of microscopic simulations: A parsimonious machine learning approach Evangelos Galaris Gianluca Fabiani I. Gallos Ioannis G. Kevrekidis Constantinos Siettos AI4CE 23 40 0 31 Jan 2022
Discovering Nonlinear PDEs from Scarce Data with Physics-encoded Learning Chengping Rao Pu Ren Yang Liu Hao Sun AI4CE 43 28 0 28 Jan 2022
Maximizing information from chemical engineering data sets: Applications to machine learning Alexander Thebelt Johannes Wiebe Jan Kronqvist Calvin Tsay Ruth Misener AI4CE 45 68 0 25 Jan 2022
Symplectic Momentum Neural Networks -- Using Discrete Variational Mechanics as a prior in Deep Learning Saul Santos Monica Ekal R. Ventura 32 5 0 20 Jan 2022