A comparative study of physics-informed neural network models for learning unknown dynamics and constitutive relations

2 April 2019

Papers citing "A comparative study of physics-informed neural network models for learning unknown dynamics and constitutive relations"

6 / 6 papers shown

Title
PhySRNet: Physics informed super-resolution network for application in computational solid mechanics Rajat Arora AI4CE 83 10 0 30 Jun 2022
Physics-informed neural networks for modeling rate- and temperature-dependent plasticity Rajat Arora P. Kakkar Biswadip Dey Amit Chakraborty PINN AI4CE 114 20 0 20 Jan 2022
HyperPINN: Learning parameterized differential equations with physics-informed hypernetworks Filipe de Avila Belbute-Peres Yi-fan Chen Fei Sha PINN 70 40 0 28 Oct 2021
Physics-constrained deep neural network method for estimating parameters in a redox flow battery Qizhi He P. Stinis A. Tartakovsky 64 34 0 21 Jun 2021
Universal Differential Equations for Scientific Machine Learning Christopher Rackauckas Yingbo Ma Julius Martensen Collin Warner K. Zubov R. Supekar Dominic J. Skinner Ali Ramadhan Alan Edelman AI4CE 115 599 0 13 Jan 2020
Discovery of Dynamics Using Linear Multistep Methods Rachael Keller Q. Du 83 36 0 29 Dec 2019