Deep Lagrangian Networks: Using Physics as Model Prior for Deep Learning

Deep Lagrangian Networks: Using Physics as Model Prior for Deep Learning

10 July 2019

Christian Ritter

Jan Peters

Papers citing "Deep Lagrangian Networks: Using Physics as Model Prior for Deep Learning"

10 / 10 papers shown

Title
A Riemannian Framework for Learning Reduced-order Lagrangian Dynamics Katharina Friedl Noémie Jaquier Jens Lundell Tamim Asfour Danica Kragic AI4CE 74 0 0 24 Oct 2024
Online Control-Informed Learning Zihao Liang Tianyu Zhou Zehui Lu Shaoshuai Mou 51 1 0 04 Oct 2024
Learning Physics From Video: Unsupervised Physical Parameter Estimation for Continuous Dynamical Systems Alejandro Castañeda Garcia Jan van Gemert Daan Brinks Nergis Tömen 49 0 0 02 Oct 2024
Forecasting Sequential Data using Consistent Koopman Autoencoders Omri Azencot N. Benjamin Erichson Vanessa Lin Michael W. Mahoney AI4TS AI4CE 87 147 0 04 Mar 2020
Graph networks as learnable physics engines for inference and control Alvaro Sanchez-Gonzalez N. Heess Jost Tobias Springenberg J. Merel Martin Riedmiller R. Hadsell Peter W. Battaglia GNN AI4CE PINN OCL 124 597 0 04 Jun 2018
Physics Informed Deep Learning (Part II): Data-driven Discovery of Nonlinear Partial Differential Equations M. Raissi P. Perdikaris George Karniadakis PINN AI4CE 47 611 0 28 Nov 2017
Physics Informed Deep Learning (Part I): Data-driven Solutions of Nonlinear Partial Differential Equations M. Raissi P. Perdikaris George Karniadakis PINN AI4CE 60 912 0 28 Nov 2017
PDE-Net: Learning PDEs from Data Zichao Long Yiping Lu Xianzhong Ma Bin Dong DiffM AI4CE 24 750 0 26 Oct 2017
DGM: A deep learning algorithm for solving partial differential equations Justin A. Sirignano K. Spiliopoulos AI4CE 54 2,042 0 24 Aug 2017
Hidden Physics Models: Machine Learning of Nonlinear Partial Differential Equations M. Raissi George Karniadakis AI4CE PINN 48 1,132 0 02 Aug 2017