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
Physics-informed deep generative models Yibo Yang P. Perdikaris AI4CE PINN 79 59 0 09 Dec 2018
Neural Ordinary Differential Equations T. Chen Yulia Rubanova J. Bettencourt David Duvenaud AI4CE 455 5,168 0 19 Jun 2018
Physics-constrained, data-driven discovery of coarse-grained dynamics L. Felsberger P. Koutsourelakis AI4CE 50 19 0 11 Feb 2018
Multistep Neural Networks for Data-driven Discovery of Nonlinear Dynamical Systems M. Raissi P. Perdikaris George Karniadakis PINN 152 266 0 04 Jan 2018
Physics Informed Deep Learning (Part II): Data-driven Discovery of Nonlinear Partial Differential Equations M. Raissi P. Perdikaris George Karniadakis PINN AI4CE 96 615 0 28 Nov 2017
DGM: A deep learning algorithm for solving partial differential equations Justin A. Sirignano K. Spiliopoulos AI4CE 97 2,067 0 24 Aug 2017