ResearchTrend.AI
Solving Newton's Equations of Motion with Large Timesteps using Recurrent Neural Networks based Operators
v1v2v3 (latest)

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

J. Kadupitiya
Geoffrey C. Fox
V. Jadhao
ArXiv (abs)PDFHTML

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

6 / 6 papers shown
Title
FlashMD: long-stride, universal prediction of molecular dynamics
FlashMD: long-stride, universal prediction of molecular dynamics
Filippo Bigi
Sanggyu Chong
Agustinus Kristiadi
Michele Ceriotti
AI4CE
50
1
0
25 May 2025
Force-Free Molecular Dynamics Through Autoregressive Equivariant Networks
Force-Free Molecular Dynamics Through Autoregressive Equivariant Networks
Fabian L. Thiemann
Thiago Reschützegger
Massimiliano Esposito
Tseden Taddese
Juan D. Olarte-Plata
Fausto Martelli
AI4CE
125
1
0
31 Mar 2025
Machine learning for advancing low-temperature plasma modeling and simulation
Machine learning for advancing low-temperature plasma modeling and simulation
J. Trieschmann
Luca Vialetto
T. Gergs
AI4CE
55
6
0
30 Jun 2023
Neural DAEs: Constrained neural networks
Neural DAEs: Constrained neural networks
Tue Boesen
E. Haber
Uri M. Ascher
103
4
0
25 Nov 2022
Exact conservation laws for neural network integrators of dynamical systems
Exact conservation laws for neural network integrators of dynamical systems
E. Müller
PINN
110
14
0
23 Sep 2022
Locally-symplectic neural networks for learning volume-preserving dynamics
Locally-symplectic neural networks for learning volume-preserving dynamics
J. Bajārs
67
11
0
19 Sep 2021