Newton vs the machine: solving the chaotic three-body problem using deep neural networks

16 October 2019

Papers citing "Newton vs the machine: solving the chaotic three-body problem using deep neural networks"

9 / 9 papers shown

Title
A hybrid approach for solving the gravitational N-body problem with Artificial Neural Networks V. S. Ulibarrena Philipp Horn S. P. Zwart E. Sellentin B. Koren Maxwell X. Cai PINN 24 2 0 31 Oct 2023
Controlling Neural Networks with Rule Representations Sungyong Seo Sercan O. Arik Jinsung Yoon Xiang Zhang Kihyuk Sohn Tomas Pfister OOD AI4CE 105 35 0 14 Jun 2021
Review: Deep Learning in Electron Microscopy Jeffrey M. Ede 191 80 0 17 Sep 2020
Hypersolvers: Toward Fast Continuous-Depth Models Michael Poli Stefano Massaroli Atsushi Yamashita Hajime Asama Jinkyoo Park BDL AI4CE 72 47 0 19 Jul 2020
Sparse Symplectically Integrated Neural Networks Daniel M. DiPietro S. Xiong Bo Zhu 88 31 0 10 Jun 2020
Adaptive Checkpoint Adjoint Method for Gradient Estimation in Neural ODE Juntang Zhuang Nicha Dvornek Xiaoxiao Li S. Tatikonda X. Papademetris James Duncan BDL 119 112 0 03 Jun 2020
When Machine Learning Meets Multiscale Modeling in Chemical Reactions Wuyue Yang Liangrong Peng Yi Zhu L. Hong AI4CE 28 12 0 01 Jun 2020
Solving Newton's Equations of Motion with Large Timesteps using Recurrent Neural Networks based Operators J. Kadupitiya Geoffrey C. Fox V. Jadhao AI4CE 70 22 0 12 Apr 2020
Depth-Width Trade-offs for ReLU Networks via Sharkovsky's Theorem Vaggos Chatziafratis Sai Ganesh Nagarajan Ioannis Panageas Tianlin Li 63 21 0 09 Dec 2019