Lagrangian PINNs: A causality-conforming solution to failure modes of physics-informed neural networks

5 May 2022

Papers citing "Lagrangian PINNs: A causality-conforming solution to failure modes of physics-informed neural networks"

7 / 7 papers shown

Title
Integration Matters for Learning PDEs with Backwards SDEs Sungje Park Stephen Tu PINN 55 0 0 02 May 2025
Fourier PINNs: From Strong Boundary Conditions to Adaptive Fourier Bases Madison Cooley Varun Shankar Robert M. Kirby Shandian Zhe 26 2 0 04 Oct 2024
SetPINNs: Set-based Physics-informed Neural Networks M. Nagda Phil Ostheimer Thomas Specht Frank Rhein F. Jirasek Stephan Mandt Marius Kloft Sophie Fellenz 3DPC PINN 46 0 0 30 Sep 2024
Gradient Flow Based Phase-Field Modeling Using Separable Neural Networks R. Mattey Susanta Ghosh AI4CE 43 1 0 09 May 2024
Macroscopic auxiliary asymptotic preserving neural networks for the linear radiative transfer equations Hongyan Li Song Jiang Wenjun Sun Liwei Xu Guanyu Zhou 27 2 0 04 Mar 2024
Explaining the physics of transfer learning a data-driven subgrid-scale closure to a different turbulent flow Adam Subel Yifei Guan A. Chattopadhyay P. Hassanzadeh AI4CE 29 41 0 07 Jun 2022
Physics-informed neural networks with hard constraints for inverse design Lu Lu R. Pestourie Wenjie Yao Zhicheng Wang F. Verdugo Steven G. Johnson PINN 39 494 0 09 Feb 2021