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Hidden Physics Models: Machine Learning of Nonlinear Partial Differential Equations

2 August 2017

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

50 / 318 papers shown

Title
Tackling the Curse of Dimensionality with Physics-Informed Neural Networks Zheyuan Hu K. Shukla George Karniadakis Kenji Kawaguchi PINN AI4CE 171 103 0 23 Jul 2023
Multigrid-Augmented Deep Learning Preconditioners for the Helmholtz Equation using Compact Implicit Layers Bar Lerer Ido Ben-Yair Eran Treister AI4CE 62 3 0 30 Jun 2023
Addressing Discontinuous Root-Finding for Subsequent Differentiability in Machine Learning, Inverse Problems, and Control Dan Johnson Ronald Fedkiw AI4CE 51 3 0 21 Jun 2023
Reversible and irreversible bracket-based dynamics for deep graph neural networks A. Gruber Kookjin Lee N. Trask AI4CE 80 10 0 24 May 2023
Stochastic PDE representation of random fields for large-scale Gaussian process regression and statistical finite element analysis Kim Jie Koh F. Cirak AI4CE 58 12 0 23 May 2023
A Survey on Solving and Discovering Differential Equations Using Deep Neural Networks Hyeonjung Jung Jung Jayant Gupta B. Jayaprakash Matthew J. Eagon Harish Selvam Carl Molnar W. Northrop Shashi Shekhar AI4CE 95 5 0 26 Apr 2023
Automatically identifying ordinary differential equations from data Kevin Egan Weizhen Li Rui Carvalho 28 2 0 21 Apr 2023
EPINN-NSE: Enhanced Physics-Informed Neural Networks for Solving Navier-Stokes Equations Ayoub Farkane Mounir Ghogho M. Oudani M. Boutayeb PINN 51 5 0 07 Apr 2023
Implementation and (Inverse Modified) Error Analysis for implicitly-templated ODE-nets Aiqing Zhu Tom S. Bertalan Beibei Zhu Yifa Tang Ioannis G. Kevrekidis 78 5 0 31 Mar 2023
Dimensionality Collapse: Optimal Measurement Selection for Low-Error Infinite-Horizon Forecasting H. Naumer F. Kamalabadi 59 0 0 27 Mar 2023
GPT-PINN: Generative Pre-Trained Physics-Informed Neural Networks toward non-intrusive Meta-learning of parametric PDEs Yanlai Chen Shawn Koohy PINN AI4CE 84 30 0 27 Mar 2023
Error Analysis of Physics-Informed Neural Networks for Approximating Dynamic PDEs of Second Order in Time Y. Qian Yongchao Zhang Yuanfei Huang S. Dong PINN 50 1 0 22 Mar 2023
Knowledge-integrated AutoEncoder Model Teddy Lazebnik Liron Simon Keren 81 5 0 12 Mar 2023
Physics-constrained neural differential equations for learning multi-ionic transport Danyal Rehman J. Lienhard AI4CE 51 6 0 07 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 94 29 0 03 Mar 2023
Physics-informed neural networks for solving forward and inverse problems in complex beam systems Taniya Kapoor Hongrui Wang A. Núñez R. Dollevoet AI4CE PINN 79 49 0 02 Mar 2023
Physics-aware deep learning framework for linear elasticity Anisha Roy Rikhi Bose AI4CE 83 8 0 19 Feb 2023
Multi-Scale Message Passing Neural PDE Solvers Léonard Equer T. Konstantin Rusch Siddhartha Mishra AI4CE 87 13 0 07 Feb 2023
An Implicit GNN Solver for Poisson-like problems Matthieu Nastorg M. Bucci T. Faney J. Gratien Guillaume Charpiat Marc Schoenauer AI4CE 95 2 0 06 Feb 2023
Recurrences reveal shared causal drivers of complex time series W. Gilpin CML AI4TS 77 8 0 31 Jan 2023
Learning Vortex Dynamics for Fluid Inference and Prediction Yitong Deng Hong-Xing Yu Jiajun Wu Bo Zhu MDE 98 20 0 27 Jan 2023
Random Grid Neural Processes for Parametric Partial Differential Equations Arnaud Vadeboncoeur Ieva Kazlauskaite Y. Papandreou F. Cirak Mark Girolami Ömer Deniz Akyildiz AI4CE 96 11 0 26 Jan 2023
Physics-informed Information Field Theory for Modeling Physical Systems with Uncertainty Quantification A. Alberts Ilias Bilionis 95 13 0 18 Jan 2023
Data-aware customization of activation functions reduces neural network error Fuchang Gao Boyu Zhang 43 4 0 16 Jan 2023
Augmented Physics-Informed Neural Networks (APINNs): A gating network-based soft domain decomposition methodology Zheyuan Hu Ameya Dilip Jagtap George Karniadakis Kenji Kawaguchi 89 85 0 16 Nov 2022
Bayesian Learning of Coupled Biogeochemical-Physical Models Abhinav Gupta Pierre FJ Lermusiaux 109 5 0 12 Nov 2022
WeakIdent: Weak formulation for Identifying Differential Equations using Narrow-fit and Trimming Mengyi Tang Wenjing Liao R. Kuske S. Kang 44 19 0 06 Nov 2022
Physics Informed Machine Learning for Chemistry Tabulation A. Salunkhe Dwyer Deighan P. DesJardin V. Chandola 37 6 0 06 Nov 2022
Physics-informed neural networks for gravity currents reconstruction from limited data Mickaël G. Delcey Y. Cheny S. Richter PINN AI4CE 91 11 0 03 Nov 2022
Agglomeration of Polygonal Grids using Graph Neural Networks with applications to Multigrid solvers P. Antonietti N. Farenga E. Manuzzi G. Martinelli L. Saverio AI4CE 50 22 0 31 Oct 2022
Partial Differential Equations Meet Deep Neural Networks: A Survey Shudong Huang Wentao Feng Chenwei Tang Jiancheng Lv AI4CE AIMat 70 21 0 27 Oct 2022
Thermodynamics-informed neural networks for physically realistic mixed reality Quercus Hernandez Alberto Badías Francisco Chinesta Elías Cueto PINN AI4CE 65 18 0 24 Oct 2022
Bayesian deep learning framework for uncertainty quantification in high dimensions Jeahan Jung Minseok Choi BDL UQCV 48 1 0 21 Oct 2022
A composable machine-learning approach for steady-state simulations on high-resolution grids Rishikesh Ranade C. Hill Lalit Ghule Jay Pathak AI4CE 73 8 0 11 Oct 2022
A Method for Computing Inverse Parametric PDE Problems with Random-Weight Neural Networks S. Dong Yiran Wang 61 21 0 09 Oct 2022
Don't Waste Data: Transfer Learning to Leverage All Data for Machine-Learnt Climate Model Emulation R. Parthipan Damon J. Wischik 78 3 0 08 Oct 2022
Deep learning for gradient flows using the Brezis-Ekeland principle Laura Carini Max Jensen R. Nürnberg 56 0 0 28 Sep 2022
A computational framework for physics-informed symbolic regression with straightforward integration of domain knowledge Liron Simon Keren A. Liberzon Teddy Lazebnik 112 83 0 13 Sep 2022
A Thermal Machine Learning Solver For Chip Simulation Rishikesh Ranade Haiyang He Jay Pathak N. Chang Akhilesh Kumar Jimin Wen 68 17 0 10 Sep 2022
Data-driven, multi-moment fluid modeling of Landau damping Wenjie Cheng H. Fu Liang Wang C. Dong Yaqiu Jin M. Jiang Jiayu Ma Yilan Qin Kexin Liu PINN AI4CE 54 12 0 10 Sep 2022
Symplectically Integrated Symbolic Regression of Hamiltonian Dynamical Systems Daniel M. DiPietro Bo Zhu 18 1 0 04 Sep 2022
DLDNN: Deterministic Lateral Displacement Design Automation by Neural Networks Farzad Vatandoust Hoseyn A. Amiri Sima Mas-hafi 11 1 0 30 Aug 2022
Semi-analytic PINN methods for singularly perturbed boundary value problems G. Gie Youngjoon Hong Chang-Yeol Jung PINN 65 6 0 19 Aug 2022
A Model-Constrained Tangent Slope Learning Approach for Dynamical Systems Hai V. Nguyen T. Bui-Thanh 56 2 0 09 Aug 2022
Fully probabilistic deep models for forward and inverse problems in parametric PDEs Arnaud Vadeboncoeur Ömer Deniz Akyildiz Ieva Kazlauskaite Mark Girolami F. Cirak AI4CE 72 18 0 09 Aug 2022
Use of BNNM for interference wave solutions of the gBS-like equation and comparison with PINNs S. Vadyala S. N. Betgeri 72 0 0 07 Aug 2022
Mining Reaction and Diffusion Dynamics in Social Activities Taichi Murayama Yasuko Matsubara Yasushi Sakurai 50 1 0 07 Aug 2022
wPINNs: Weak Physics informed neural networks for approximating entropy solutions of hyperbolic conservation laws Tim De Ryck Siddhartha Mishra Roberto Molinaro PINN 77 32 0 18 Jul 2022
Physics-Aware Neural Networks for Boundary Layer Linear Problems A. A. Gomes Larissa Miguez da Silva F. Valentin PINN AI4CE 11 1 0 15 Jul 2022
Error analysis for deep neural network approximations of parametric hyperbolic conservation laws Tim De Ryck Siddhartha Mishra PINN 56 12 0 15 Jul 2022