How to Avoid Trivial Solutions in Physics-Informed Neural Networks

10 December 2021

Papers citing "How to Avoid Trivial Solutions in Physics-Informed Neural Networks"

6 / 6 papers shown

Title
Transport-Embedded Neural Architecture: Redefining the Landscape of physics aware neural models in fluid mechanics Amirmahdi Jafari 33 0 0 05 Oct 2024
SetPINNs: Set-based Physics-informed Neural Networks Mayank Nagda Phil Ostheimer Thomas Specht Frank Rhein Fabian Jirasek Stephan Mandt Marius Kloft Sophie Fellenz 3DPC PINN 46 0 0 30 Sep 2024
Generating Physical Dynamics under Priors Zihan Zhou Xiaoxue Wang Tianshu Yu DiffM AI4CE 72 0 0 01 Sep 2024
Physical Activation Functions (PAFs): An Approach for More Efficient Induction of Physics into Physics-Informed Neural Networks (PINNs) J. Abbasi Paal Ostebo Andersen PINN AI4CE 25 14 0 29 May 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 41 17 0 25 Mar 2022
Fourier Neural Operator for Parametric Partial Differential Equations Zong-Yi Li Nikola B. Kovachki Kamyar Azizzadenesheli Burigede Liu K. Bhattacharya Andrew M. Stuart Anima Anandkumar AI4CE 247 2,298 0 18 Oct 2020