Certified machine learning: A posteriori error estimation for physics-informed neural networks

31 March 2022

Papers citing "Certified machine learning: A posteriori error estimation for physics-informed neural networks"

7 / 7 papers shown

Title
DeepSPoC: A Deep Learning-Based PDE Solver Governed by Sequential Propagation of Chaos Kai Du Yongle Xie Tao Zhou Yuancheng Zhou 21 0 0 29 Aug 2024
Error estimation for physics-informed neural networks with implicit Runge-Kutta methods Jochen Stiasny Spyros Chatzivasileiadis PINN 20 1 0 10 Jan 2024
Efficient Error Certification for Physics-Informed Neural Networks Francisco Eiras Adel Bibi Rudy Bunel Krishnamurthy Dvijotham Philip H. S. Torr M. P. Kumar PINN 24 1 0 17 May 2023
Certified machine learning: Rigorous a posteriori error bounds for PDE defined PINNs Birgit Hillebrecht B. Unger PINN 11 5 0 07 Oct 2022
Generic bounds on the approximation error for physics-informed (and) operator learning Tim De Ryck Siddhartha Mishra PINN 59 59 0 23 May 2022
Lagrangian PINNs: A causality-conforming solution to failure modes of physics-informed neural networks R. Mojgani Maciej Balajewicz P. Hassanzadeh PINN 25 45 0 05 May 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 26 1,177 0 14 Jan 2022