Physics-Informed Machine Learning: A Survey on Problems, Methods and Applications

15 November 2022

Hang Su

Jun Zhu

PINN

AI4CE

ArXiv PDF HTML

Papers citing "Physics-Informed Machine Learning: A Survey on Problems, Methods and Applications"

31 / 31 papers shown

Title
Receding Hamiltonian-Informed Optimal Neural Control and State Estimation for Closed-Loop Dynamical Systems Josue N. Rivera Dengfeng Sun 23 0 0 02 Nov 2024
Gradient Flow Based Phase-Field Modeling Using Separable Neural Networks R. Mattey Susanta Ghosh AI4CE 27 1 0 09 May 2024
From Spectra to Biophysical Insights: End-to-End Learning with a Biased Radiative Transfer Model Yihang She Clement Atzberger Andrew Blake Srinivasan Keshav 16 0 0 05 Mar 2024
Physics-Informed Computer Vision: A Review and Perspectives C. Banerjee Kien Nguyen Clinton Fookes G. Karniadakis PINN AI4CE 25 27 0 29 May 2023
Equivariant Energy-Guided SDE for Inverse Molecular Design Fan Bao Min Zhao Zhongkai Hao Pei‐Yun Li Chongxuan Li Jun Zhu DiffM 162 62 0 30 Sep 2022
Fourier Neural Operator with Learned Deformations for PDEs on General Geometries Zong-Yi Li Daniel Zhengyu Huang Burigede Liu Anima Anandkumar AI4CE 105 243 0 11 Jul 2022
D-Grasp: Physically Plausible Dynamic Grasp Synthesis for Hand-Object Interactions Sammy Christen Muhammed Kocabas Emre Aksan Jemin Hwangbo Jie Song Otmar Hilliges 106 104 0 01 Dec 2021
Masked Autoencoders Are Scalable Vision Learners Kaiming He Xinlei Chen Saining Xie Yanghao Li Piotr Dollár Ross B. Girshick ViT TPM 258 7,337 0 11 Nov 2021
Solving PDE-constrained Control Problems Using Operator Learning Rakhoon Hwang Jae Yong Lee J. Shin H. Hwang AI4CE 107 43 0 09 Nov 2021
Improved architectures and training algorithms for deep operator networks Sifan Wang Hanwen Wang P. Perdikaris AI4CE 37 102 0 04 Oct 2021
Multiwavelet-based Operator Learning for Differential Equations Gaurav Gupta Xiongye Xiao P. Bogdan 115 198 0 28 Sep 2021
Arbitrary-Depth Universal Approximation Theorems for Operator Neural Networks Annan Yu Chloe Becquey Diana Halikias Matthew Esmaili Mallory Alex Townsend 51 7 0 23 Sep 2021
Physics-based Deep Learning Nils Thuerey Philipp Holl P. Holl Patrick Schnell Felix Trost Kiwon Um P. Schnell F. Trost PINN AI4CE 48 89 0 11 Sep 2021
Finite Basis Physics-Informed Neural Networks (FBPINNs): a scalable domain decomposition approach for solving differential equations Benjamin Moseley Andrew Markham T. Nissen‐Meyer PINN 35 206 0 16 Jul 2021
Meta-learning PINN loss functions Apostolos F. Psaros Kenji Kawaguchi George Karniadakis PINN 20 73 0 12 Jul 2021
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges M. Bronstein Joan Bruna Taco S. Cohen Petar Velivcković GNN 161 1,095 0 27 Apr 2021
Efficient training of physics-informed neural networks via importance sampling M. A. Nabian R. J. Gladstone Hadi Meidani DiffM PINN 55 218 0 26 Apr 2021
Parallel Physics-Informed Neural Networks via Domain Decomposition K. Shukla Ameya Dilip Jagtap George Karniadakis PINN 88 214 0 20 Apr 2021
Physics-informed neural networks with hard constraints for inverse design Lu Lu R. Pestourie Wenjie Yao Zhicheng Wang F. Verdugo Steven G. Johnson PINN 39 365 0 09 Feb 2021
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 126 435 0 18 Dec 2020
Fourier Neural Operator for Parametric Partial Differential Equations Zong-Yi Li Nikola B. Kovachki Kamyar Azizzadenesheli Burigede Liu K. Bhattacharya Andrew M. Stuart Anima Anandkumar AI4CE 197 2,254 0 18 Oct 2020
Multi-scale Deep Neural Network (MscaleDNN) for Solving Poisson-Boltzmann Equation in Complex Domains Ziqi Liu Wei Cai Zhi-Qin John Xu AI4CE 109 122 0 22 Jul 2020
hp-VPINNs: Variational Physics-Informed Neural Networks With Domain Decomposition E. Kharazmi Zhongqiang Zhang George Karniadakis 104 503 0 11 Mar 2020
Integrating Scientific Knowledge with Machine Learning for Engineering and Environmental Systems J. Willard X. Jia Shaoming Xu M. Steinbach Vipin Kumar AI4CE 80 285 0 10 Mar 2020
Lagrangian Neural Networks M. Cranmer S. Greydanus Stephan Hoyer Peter W. Battaglia D. Spergel S. Ho PINN 118 364 0 10 Mar 2020
Measurement-based adaptation protocol with quantum reinforcement learning in a Rigetti quantum computer Julio Olivares-Sánchez J. Casanova Enrique Solano L. Lamata 14 36 0 19 Nov 2018
Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation Jiaxuan You Bowen Liu Rex Ying Vijay S. Pande J. Leskovec GNN 181 878 0 07 Jun 2018
Junction Tree Variational Autoencoder for Molecular Graph Generation Wengong Jin Regina Barzilay Tommi Jaakkola 208 1,205 0 12 Feb 2018
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation C. Qi Hao Su Kaichun Mo Leonidas J. Guibas 3DH 3DPC 3DV PINN 210 13,886 0 02 Dec 2016
Interaction Networks for Learning about Objects, Relations and Physics Peter W. Battaglia Razvan Pascanu Matthew Lai Danilo Jimenez Rezende Koray Kavukcuoglu AI4CE OCL PINN GNN 252 1,394 0 01 Dec 2016
Stochastic Gradient Descent for Non-smooth Optimization: Convergence Results and Optimal Averaging Schemes Ohad Shamir Tong Zhang 99 570 0 08 Dec 2012