Respecting causality is all you need for training physics-informed neural networks

14 March 2022

Papers citing "Respecting causality is all you need for training physics-informed neural networks"

50 / 122 papers shown

Title
An operator preconditioning perspective on training in physics-informed machine learning Tim De Ryck Florent Bonnet Siddhartha Mishra Emmanuel de Bezenac AI4CE 41 14 0 09 Oct 2023
Physics-aware Machine Learning Revolutionizes Scientific Paradigm for Machine Learning and Process-based Hydrology Qingsong Xu Yilei Shi Jonathan Bamber Ye Tuo Ralf Ludwig Xiao Xiang Zhu AI4CE 20 10 0 08 Oct 2023
Investigating the Ability of PINNs To Solve Burgers' PDE Near Finite-Time BlowUp Dibyakanti Kumar Anirbit Mukherjee 31 2 0 08 Oct 2023
Randomized Sparse Neural Galerkin Schemes for Solving Evolution Equations with Deep Networks Jules Berman Benjamin Peherstorfer 26 13 0 07 Oct 2023
Spectral operator learning for parametric PDEs without data reliance Junho Choi Taehyun Yun Namjung Kim Youngjoon Hong 19 8 0 03 Oct 2023
Improving physics-informed DeepONets with hard constraints Rudiger Brecht D. Popovych Alexander Bihlo R. Popovych AI4CE 18 8 0 14 Sep 2023
Physics-Informed Neural Networks for an optimal counterdiabatic quantum computation Antonio Ferrer-Sánchez Carlos Flores-Garrigós C. Hernani-Morales José J. Orquín-Marqués N. N. Hegade Alejandro Gomez Cadavid Iraitz Montalban Enrique Solano Yolanda Vives-Gilabert J. D. Martín-Guerrero 32 2 0 08 Sep 2023
Neural oscillators for generalization of physics-informed machine learning Taniya Kapoor Abhishek Chandra D. Tartakovsky Hongrui Wang Alfredo Núñez R. Dollevoet AI4CE 29 11 0 17 Aug 2023
An Expert's Guide to Training Physics-informed Neural Networks Sizhuang He Shyam Sankaran Hanwen Wang P. Perdikaris PINN 28 97 0 16 Aug 2023
A Sequential Meta-Transfer (SMT) Learning to Combat Complexities of Physics-Informed Neural Networks: Application to Composites Autoclave Processing Milad Ramezankhani A. Milani PINN 24 4 0 12 Aug 2023
Learning Specialized Activation Functions for Physics-informed Neural Networks Honghui Wang Lu Lu Shiji Song Gao Huang PINN AI4CE 16 11 0 08 Aug 2023
Residual-based attention and connection to information bottleneck theory in PINNs Sokratis J. Anagnostopoulos Juan Diego Toscano Nikos Stergiopulos George Karniadakis 25 20 0 01 Jul 2023
Parameter Identification for Partial Differential Equations with Spatiotemporal Varying Coefficients Guangtao Zhang Yiting Duan Guanyu Pan Qijing Chen Huiyu Yang Zhikun Zhang 17 0 0 30 Jun 2023
Separable Physics-Informed Neural Networks Junwoo Cho Seungtae Nam Hyunmo Yang S. Yun Youngjoon Hong Eunbyung Park PINN AI4CE 17 43 0 28 Jun 2023
PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs Zhongkai Hao J. Yao Chang Su Hang Su Ziao Wang ... Zeyu Xia Yichi Zhang Songming Liu Lu Lu Jun Zhu PINN 29 30 0 15 Jun 2023
Data driven localized wave solution of the Fokas-Lenells equation using modified PINN G. K. Saharia Sagardeep Talukdar Riki Dutta S. Nandy 13 1 0 03 Jun 2023
Scalable Transformer for PDE Surrogate Modeling Zijie Li Dule Shu A. Farimani 35 67 0 27 May 2023
Learning from Integral Losses in Physics Informed Neural Networks Ehsan Saleh Saba Ghaffari Timothy Bretl Luke N. Olson Matthew West PINN AI4CE 30 4 0 27 May 2023
Reconstruction, forecasting, and stability of chaotic dynamics from partial data Elise Özalp G. Margazoglou Luca Magri AI4TS 18 10 0 24 May 2023
ParticleWNN: a Novel Neural Networks Framework for Solving Partial Differential Equations Yaohua Zang Gang Bao 29 4 0 21 May 2023
LatentPINNs: Generative physics-informed neural networks via a latent representation learning M. H. Taufik T. Alkhalifah AI4CE DiffM 49 4 0 11 May 2023
Neural Steerer: Novel Steering Vector Synthesis with a Causal Neural Field over Frequency and Source Positions Diego Di Carlo Aditya Arie Nugraha Mathieu Fontaine Yoshiaki Bando Kazuyoshi Yoshii LLMSV 24 0 0 08 May 2023
M-ENIAC: A machine learning recreation of the first successful numerical weather forecasts Rudiger Brecht Alexander Bihlo 29 4 0 18 Apr 2023
Microseismic source imaging using physics-informed neural networks with hard constraints Xinquan Huang T. Alkhalifah 34 7 0 09 Apr 2023
About optimal loss function for training physics-informed neural networks under respecting causality V. A. Es'kin Danil V. Davydov Ekaterina D. Egorova Alexey O. Malkhanov Mikhail A. Akhukov Mikhail E. Smorkalov PINN 16 7 0 05 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
Improving physics-informed neural networks with meta-learned optimization Alexander Bihlo PINN 36 18 0 13 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
A unified scalable framework for causal sweeping strategies for Physics-Informed Neural Networks (PINNs) and their temporal decompositions Michael Penwarden Ameya Dilip Jagtap Shandian Zhe George Karniadakis Robert M. Kirby PINN AI4CE 23 57 0 28 Feb 2023
Achieving High Accuracy with PINNs via Energy Natural Gradients Johannes Müller Marius Zeinhofer 13 4 0 25 Feb 2023
On the Generalization of PINNs outside the training domain and the Hyperparameters influencing it Andrea Bonfanti Roberto Santana M. Ellero Babak Gholami AI4CE PINN 43 3 0 15 Feb 2023
Failure-informed adaptive sampling for PINNs, Part II: combining with re-sampling and subset simulation Zhi-Hao Gao Tao Tang Liang Yan Tao Zhou 37 18 0 03 Feb 2023
LSA-PINN: Linear Boundary Connectivity Loss for Solving PDEs on Complex Geometry Jian Cheng Wong P. Chiu C. Ooi M. Dao Yew-Soon Ong AI4CE PINN 22 10 0 03 Feb 2023
Neural Control of Parametric Solutions for High-dimensional Evolution PDEs Nathan Gaby X. Ye Haomin Zhou 13 6 0 31 Jan 2023
Spatio-Temporal Super-Resolution of Dynamical Systems using Physics-Informed Deep-Learning Rajat Arora Ankit Shrivastava AI4CE 36 4 0 08 Dec 2022
Bayesian Physics Informed Neural Networks for Data Assimilation and Spatio-Temporal Modelling of Wildfires J. Dabrowski D. Pagendam J. Hilton Conrad Sanderson Dan MacKinlay C. Huston Andrew Bolt Petra Kuhnert PINN 33 17 0 02 Dec 2022
VI-PINNs: Variance-involved Physics-informed Neural Networks for Fast and Accurate Prediction of Partial Differential Equations Bin Shan Ye Li Sheng-Jun Huang PINN 26 2 0 30 Nov 2022
Physics-informed Neural Networks with Unknown Measurement Noise Philipp Pilar Niklas Wahlström PINN 23 6 0 28 Nov 2022
Neural tangent kernel analysis of PINN for advection-diffusion equation M. Saadat B. Gjorgiev L. Das G. Sansavini 33 0 0 21 Nov 2022
Convergence analysis of unsupervised Legendre-Galerkin neural networks for linear second-order elliptic PDEs Seungchan Ko S. Yun Youngjoon Hong 17 5 0 16 Nov 2022
Separable PINN: Mitigating the Curse of Dimensionality in Physics-Informed Neural Networks Junwoo Cho Seungtae Nam Hyunmo Yang S. Yun Youngjoon Hong Eunbyung Park PINN AI4CE 23 8 0 16 Nov 2022
Physics-Informed Machine Learning: A Survey on Problems, Methods and Applications Zhongkai Hao Songming Liu Yichi Zhang Chengyang Ying Yao Feng Hang Su Jun Zhu PINN AI4CE 35 89 0 15 Nov 2022
Meta-PDE: Learning to Solve PDEs Quickly Without a Mesh Tian Qin Alex Beatson Deniz Oktay N. McGreivy Ryan P. Adams AI4CE 19 10 0 03 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
A Novel Adaptive Causal Sampling Method for Physics-Informed Neural Networks Jia Guo Haifeng Wang Chenping Hou 11 7 0 24 Oct 2022
Robust Regression with Highly Corrupted Data via Physics Informed Neural Networks Wei Peng Wenjuan Yao Weien Zhou Xiaoya Zhang Weijie Yao PINN 50 5 0 19 Oct 2022
Tunable Complexity Benchmarks for Evaluating Physics-Informed Neural Networks on Coupled Ordinary Differential Equations Alexander New B. Eng A. Timm A. Gearhart 20 4 0 14 Oct 2022
Random Weight Factorization Improves the Training of Continuous Neural Representations Sizhuang He Hanwen Wang Jacob H. Seidman P. Perdikaris 26 10 0 03 Oct 2022
Failure-informed adaptive sampling for PINNs Zhiwei Gao Liang Yan Tao Zhou 18 77 0 01 Oct 2022
Residual-Quantile Adjustment for Adaptive Training of Physics-informed Neural Network Jiayue Han Zhiqiang Cai Zhiyou Wu Xiang Zhou 44 7 0 09 Sep 2022