Neural Parameter Regression for Explicit Representations of PDE Solution Operators

19 March 2024

Papers citing "Neural Parameter Regression for Explicit Representations of PDE Solution Operators"

6 / 6 papers shown

Title
PERP: Rethinking the Prune-Retrain Paradigm in the Era of LLMs Max Zimmer Megi Andoni Christoph Spiegel S. Pokutta VLM 23 7 0 23 Dec 2023
Adaptive physics-informed neural operator for coarse-grained non-equilibrium flows Ivan Zanardi Simone Venturi M. Panesi AI4CE 39 12 0 27 Oct 2022
Generic bounds on the approximation error for physics-informed (and) operator learning Tim De Ryck Siddhartha Mishra PINN 46 49 0 23 May 2022
Improved architectures and training algorithms for deep operator networks Sifan Wang Hanwen Wang P. Perdikaris AI4CE 22 79 0 04 Oct 2021
Finite Basis Physics-Informed Neural Networks (FBPINNs): a scalable domain decomposition approach for solving differential equations Benjamin Moseley Andrew Markham T. Nissen‐Meyer PINN 30 131 0 16 Jul 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 26 365 0 09 Feb 2021