Inverse-Dirichlet Weighting Enables Reliable Training of Physics Informed Neural Networks

2 July 2021

Papers citing "Inverse-Dirichlet Weighting Enables Reliable Training of Physics Informed Neural Networks"

30 / 30 papers shown

Title
Reliable and Efficient Inverse Analysis using Physics-Informed Neural Networks with Distance Functions and Adaptive Weight Tuning Shota Deguchi Mitsuteru Asai PINN AI4CE 81 0 0 25 Apr 2025
Solving 2-D Helmholtz equation in the rectangular, circular, and elliptical domains using neural networks D. Veerababu Prasanta K. Ghosh 70 0 0 26 Mar 2025
Estimation of the Acoustic Field in a Uniform Duct with Mean Flow using Neural Networks D. Veerababu Prasanta K. Ghosh AI4CE 42 0 0 25 Mar 2025
Sample-Efficient Reinforcement Learning of Koopman eNMPC Daniel Mayfrank M. Velioglu Alexander Mitsos Manuel Dahmen OffRL 41 0 0 24 Mar 2025
A physics-informed transformer neural operator for learning generalized solutions of initial boundary value problems Sumanth Kumar Boya Deepak Subramani AI4CE 94 0 0 12 Dec 2024
HyResPINNs: Hybrid Residual Networks for Adaptive Neural and RBF Integration in Solving PDEs Madison Cooley Robert M. Kirby Shandian Zhe Varun Shankar PINN AI4CE 23 0 0 04 Oct 2024
Functional Tensor Decompositions for Physics-Informed Neural Networks Sai Karthikeya Vemuri Tim Buchner Julia Niebling Joachim Denzler PINN 38 4 0 23 Aug 2024
Adapting Physics-Informed Neural Networks to Improve ODE Optimization in Mosquito Population Dynamics D. V. Cuong Branislava Lalić Mina Petrić Binh Nguyen M. Roantree PINN AI4CE 47 0 0 07 Jun 2024
Physics-Informed Neural Networks for Dynamic Process Operations with Limited Physical Knowledge and Data M. Velioglu Song Zhai Sophia Rupprecht Alexander Mitsos Andreas Jupke Manuel Dahmen PINN AI4CE 44 4 0 03 Jun 2024
RoPINN: Region Optimized Physics-Informed Neural Networks Haixu Wu Huakun Luo Yuezhou Ma Jianmin Wang Mingsheng Long AI4CE 32 6 0 23 May 2024
BiLO: Bilevel Local Operator Learning for PDE inverse problems Ray Zirui Zhang Xiaohui Xie John S. Lowengrub 68 1 0 27 Apr 2024
PirateNets: Physics-informed Deep Learning with Residual Adaptive Networks Sifan Wang Bowen Li Yuhan Chen P. Perdikaris AI4CE PINN 21 27 0 01 Feb 2024
Personalized Predictions of Glioblastoma Infiltration: Mathematical Models, Physics-Informed Neural Networks and Multimodal Scans Ray Zirui Zhang Ivan Ezhov Michal Balcerak Andy Zhu Benedikt Wiestler Bjoern H. Menze John S. Lowengrub AI4CE 47 6 0 28 Nov 2023
Stochastic force inference via density estimation Victor Chardès S. Maddu Michael J. Shelley DiffM 11 3 0 03 Oct 2023
Auto-weighted Bayesian Physics-Informed Neural Networks and robust estimations for multitask inverse problems in pore-scale imaging of dissolution S. Pérez P. Poncet 25 3 0 24 Aug 2023
An Expert's Guide to Training Physics-informed Neural Networks Sifan Wang Shyam Sankaran Hanwen Wang P. Perdikaris PINN 28 96 0 16 Aug 2023
Learning locally dominant force balances in active particle systems D. Sturm S. Maddu I. Sbalzarini 11 1 0 27 Jul 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 29 0 15 Jun 2023
Maximum-likelihood Estimators in Physics-Informed Neural Networks for High-dimensional Inverse Problems G. S. Gusmão A. Medford PINN 12 8 0 12 Apr 2023
PINN Training using Biobjective Optimization: The Trade-off between Data Loss and Residual Loss Fabian Heldmann Sarah Treibert Matthias Ehrhardt K. Klamroth 30 20 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
Learning Partial Differential Equations by Spectral Approximates of General Sobolev Spaces Juan Esteban Suarez Cardona Phil-Alexander Hofmann Michael Hecht 11 2 0 12 Jan 2023
Replacing Automatic Differentiation by Sobolev Cubatures fastens Physics Informed Neural Nets and strengthens their Approximation Power Juan Esteban Suarez Cardona Michael Hecht 14 4 0 23 Nov 2022
Physics-Informed Koopman Network Yuying Liu A. Sholokhov Hassan Mansour S. Nabi AI4CE 23 3 0 17 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 23 89 0 15 Nov 2022
Tunable Complexity Benchmarks for Evaluating Physics-Informed Neural Networks on Coupled Ordinary Differential Equations Alexander New B. Eng A. Timm A. Gearhart 14 4 0 14 Oct 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 36 17 0 25 Mar 2022
Respecting causality is all you need for training physics-informed neural networks Sifan Wang Shyam Sankaran P. Perdikaris PINN CML AI4CE 30 199 0 14 Mar 2022
Data vs. Physics: The Apparent Pareto Front of Physics-Informed Neural Networks Franz M. Rohrhofer S. Posch C. Gößnitzer Bernhard C. Geiger PINN 23 39 0 03 May 2021
B-PINNs: Bayesian Physics-Informed Neural Networks for Forward and Inverse PDE Problems with Noisy Data Liu Yang Xuhui Meng George Karniadakis PINN 177 758 0 13 Mar 2020