On the Completeness of Invariant Geometric Deep Learning Models

7 February 2024

Papers citing "On the Completeness of Invariant Geometric Deep Learning Models"

8 / 8 papers shown

Title
Geometric Representation Condition Improves Equivariant Molecule Generation Zian Li Cai Zhou Xiyuan Wang Xingang Peng Muhan Zhang 35 1 0 04 Oct 2024
On the Expressive Power of Sparse Geometric MPNNs Yonatan Sverdlov Nadav Dym 40 1 0 02 Jul 2024
Weisfeiler Leman for Euclidean Equivariant Machine Learning Snir Hordan Tal Amir Nadav Dym 41 5 0 04 Feb 2024
Three iterations of $(d-1)$ -WL test distinguish non isometric clouds of $d$ -dimensional points Valentino Delle Rose A. Kozachinskiy Cristóbal Rojas Mircea Petrache Pablo Barceló 21 8 0 22 Mar 2023
Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs Yi-Lun Liao Tess E. Smidt 73 142 0 23 Jun 2022
Frame Averaging for Invariant and Equivariant Network Design Omri Puny Matan Atzmon Heli Ben-Hamu Ishan Misra Aditya Grover Edward James Smith Y. Lipman FedML 33 123 0 07 Oct 2021
Vector Neurons: A General Framework for SO(3)-Equivariant Networks Congyue Deng Or Litany Yueqi Duan A. Poulenard Andrea Tagliasacchi Leonidas J. Guibas 3DPC 96 264 0 25 Apr 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 183 1,218 0 08 Jan 2021