Solving Newton's Equations of Motion with Large Timesteps using Recurrent Neural Networks based Operators

12 April 2020

Papers citing "Solving Newton's Equations of Motion with Large Timesteps using Recurrent Neural Networks based Operators"

7 / 7 papers shown

Title
Force-Free Molecular Dynamics Through Autoregressive Equivariant Networks Fabian L. Thiemann Thiago Reschützegger Massimiliano Esposito Tseden Taddese Juan D. Olarte-Plata Fausto Martelli AI4CE 61 0 0 31 Mar 2025
Neural DAEs: Constrained neural networks Tue Boesen E. Haber Uri M. Ascher 44 3 0 25 Nov 2022
Exact conservation laws for neural network integrators of dynamical systems E. Müller PINN 54 12 0 23 Sep 2022
Locally-symplectic neural networks for learning volume-preserving dynamics J. Bajārs 34 9 0 19 Sep 2021
Lagrangian Neural Networks M. Cranmer S. Greydanus Stephan Hoyer Peter W. Battaglia D. Spergel S. Ho PINN 139 425 0 10 Mar 2020
Symplectic Recurrent Neural Networks Zhengdao Chen Jianyu Zhang Martín Arjovsky Léon Bottou 152 221 0 29 Sep 2019
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation Yonghui Wu M. Schuster Zhehuai Chen Quoc V. Le Mohammad Norouzi ... Alex Rudnick Oriol Vinyals G. Corrado Macduff Hughes J. Dean AIMat 718 6,750 0 26 Sep 2016