Accelerating the prediction of inorganic surfaces with machine learning interatomic potentials

18 December 2023

Papers citing "Accelerating the prediction of inorganic surfaces with machine learning interatomic potentials"

4 / 4 papers shown

Title
Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs Yi-Lun Liao Tess E. Smidt 75 211 0 23 Jun 2022
Nested sampling for physical scientists G. Ashton N. Bernstein Johannes Buchner Xi Chen Gábor Csányi ... Leah F. South J. Veitch Philipp Wacker D. Wales David Yallup 31 75 0 31 May 2022
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 188 1,218 0 08 Jan 2021
The Open Catalyst 2020 (OC20) Dataset and Community Challenges L. Chanussot Abhishek Das Siddharth Goyal Thibaut Lavril Muhammed Shuaibi ... Brandon M. Wood Junwoong Yoon Devi Parikh C. L. Zitnick Zachary W. Ulissi 218 498 0 20 Oct 2020