TeaNet: universal neural network interatomic potential inspired by
iterative electronic relaxations

TeaNet: universal neural network interatomic potential inspired by iterative electronic relaxations

2 December 2019

Papers citing "TeaNet: universal neural network interatomic potential inspired by iterative electronic relaxations"

10 / 10 papers shown

Title
A practical guide to machine learning interatomic potentials -- Status and future Ryan Jacobs D. Morgan Siamak Attarian Jun Meng Chen Shen ... K. J. Schmidt So Takamoto Aidan Thompson Julia Westermayr Brandon M. Wood 59 4 0 12 Mar 2025
Neural Network Matrix Product Operator: A Multi-Dimensionally Integrable Machine Learning Potential Kentaro Hino Yuki Kurashige 34 0 0 31 Oct 2024
Molecule Graph Networks with Many-body Equivariant Interactions Zetian Mao Jiawen Li Chen Liang Diptesh Das Masato Sumita Koji Tsuda Kelin Xia Koji Tsuda 35 1 0 19 Jun 2024
FeNNol: an Efficient and Flexible Library for Building Force-field-enhanced Neural Network Potentials Thomas Plé Olivier Adjoua Louis Lagardère Jean‐Philip Piquemal 32 8 0 02 May 2024
Crystal structure prediction using neural network potential and age-fitness Pareto genetic algorithm Sadman Sadeed Omee Lai Wei Jianjun Hu 14 7 0 13 Sep 2023
SpookyNet: Learning Force Fields with Electronic Degrees of Freedom and Nonlocal Effects Oliver T. Unke Stefan Chmiela M. Gastegger Kristof T. Schütt H. E. Sauceda K. Müller 174 246 0 01 May 2021
E(3)-Equivariant Graph Neural Networks for Data-Efficient and Accurate Interatomic Potentials Simon L. Batzner Albert Musaelian Lixin Sun Mario Geiger J. Mailoa M. Kornbluth N. Molinari Tess E. Smidt Boris Kozinsky 206 1,240 0 08 Jan 2021
Symmetry-adapted graph neural networks for constructing molecular dynamics force fields Zun Wang Chong Wang Sibo Zhao Shiqiao Du Yong Xu B. Gu W. Duan AI4CE 27 14 0 08 Jan 2021
Geometric deep learning: going beyond Euclidean data M. Bronstein Joan Bruna Yann LeCun Arthur Szlam P. Vandergheynst GNN 259 3,239 0 24 Nov 2016
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation Yonghui Wu M. Schuster Z. Chen Quoc V. Le Mohammad Norouzi ... Alex Rudnick Oriol Vinyals G. Corrado Macduff Hughes J. Dean AIMat 716 6,743 0 26 Sep 2016