PhAST: Physics-Aware, Scalable, and Task-specific GNNs for Accelerated
Catalyst Design

PhAST: Physics-Aware, Scalable, and Task-specific GNNs for Accelerated Catalyst Design

22 November 2022

Alexandre Duval

Alex Hernández-García

Papers citing "PhAST: Physics-Aware, Scalable, and Task-specific GNNs for Accelerated Catalyst Design"

5 / 5 papers shown

Title
On the importance of catalyst-adsorbate 3D interactions for relaxed energy predictions Alvaro Carbonero Alexandre Duval Victor Schmidt Santiago Miret Alex Hernandez-Garcia Yoshua Bengio David Rolnick 25 0 0 10 Oct 2023
FAENet: Frame Averaging Equivariant GNN for Materials Modeling Alexandre Duval Victor Schmidt A. Garcia Santiago Miret Fragkiskos D. Malliaros Yoshua Bengio David Rolnick 20 52 0 28 Apr 2023
Spherical Channels for Modeling Atomic Interactions C. L. Zitnick Abhishek Das Adeesh Kolluru Janice Lan Muhammed Shuaibi Anuroop Sriram Zachary W. Ulissi Brandon M. Wood 79 57 0 29 Jun 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 190 1,229 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 221 498 0 20 Oct 2020