Improved Training of Physics-Informed Neural Networks with Model Ensembles

11 April 2022

Papers citing "Improved Training of Physics-Informed Neural Networks with Model Ensembles"

14 / 14 papers shown

Title
Learning and discovering multiple solutions using physics-informed neural networks with random initialization and deep ensemble Zongren Zou Zhicheng Wang George Karniadakis PINN AI4CE 65 2 0 08 Mar 2025
Symplectic Neural Flows for Modeling and Discovery Priscilla Canizares Davide Murari Carola-Bibiane Schönlieb Ferdia Sherry Zakhar Shumaylov 80 1 0 21 Dec 2024
Label Propagation Training Schemes for Physics-Informed Neural Networks and Gaussian Processes Ming Zhong Dehao Liu Raymundo Arroyave U. Braga-Neto AI4CE SSL 13 1 0 08 Apr 2024
Approximating Families of Sharp Solutions to Fisher's Equation with Physics-Informed Neural Networks Franz M. Rohrhofer S. Posch C. Gößnitzer Bernhard C. Geiger 19 1 0 13 Feb 2024
The Challenges of the Nonlinear Regime for Physics-Informed Neural Networks Andrea Bonfanti Giuseppe Bruno Cristina Cipriani 24 7 0 06 Feb 2024
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 18 9 0 08 Oct 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 32 3 0 15 Feb 2023
Residual-Quantile Adjustment for Adaptive Training of Physics-informed Neural Network Jiayue Han Zhiqiang Cai Zhiyou Wu Xiang Zhou 42 7 0 09 Sep 2022
A comprehensive study of non-adaptive and residual-based adaptive sampling for physics-informed neural networks Chen-Chun Wu M. Zhu Qinyan Tan Yadhu Kartha Lu Lu 21 351 0 21 Jul 2022
Scientific Machine Learning through Physics-Informed Neural Networks: Where we are and What's next S. Cuomo Vincenzo Schiano Di Cola F. Giampaolo G. Rozza Maizar Raissi F. Piccialli PINN 24 1,170 0 14 Jan 2022
Parallel Physics-Informed Neural Networks via Domain Decomposition K. Shukla Ameya Dilip Jagtap George Karniadakis PINN 101 272 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 39 493 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 131 438 0 18 Dec 2020
Improving neural networks by preventing co-adaptation of feature detectors Geoffrey E. Hinton Nitish Srivastava A. Krizhevsky Ilya Sutskever Ruslan Salakhutdinov VLM 243 7,620 0 03 Jul 2012