Is Distance Matrix Enough for Geometric Deep Learning?

11 February 2023

Papers citing "Is Distance Matrix Enough for Geometric Deep Learning?"

31 / 31 papers shown

Title
Geometric Representation Condition Improves Equivariant Molecule Generation Zian Li Cai Zhou Xiyuan Wang Xingang Peng Muhan Zhang 61 2 0 04 Oct 2024
On the Expressive Power of Sparse Geometric MPNNs Yonatan Sverdlov Nadav Dym 79 3 0 02 Jul 2024
Boosting the Cycle Counting Power of Graph Neural Networks with I $^2$ -GNNs Yinan Huang Xingang Peng Jianzhu Ma Muhan Zhang 108 48 0 22 Oct 2022
MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields Ilyes Batatia D. P. Kovács G. Simm Christoph Ortner Gábor Csányi 77 480 0 15 Jun 2022
Learning Local Equivariant Representations for Large-Scale Atomistic Dynamics Albert Musaelian Simon L. Batzner A. Johansson Lixin Sun Cameron J. Owen M. Kornbluth Boris Kozinsky 89 452 0 11 Apr 2022
SpeqNets: Sparsity-aware Permutation-equivariant Graph Networks Christopher Morris Gaurav Rattan Sandra Kiefer Siamak Ravanbakhsh 80 40 0 25 Mar 2022
TorchMD-NET: Equivariant Transformers for Neural Network based Molecular Potentials Philipp Thölke Gianni De Fabritiis AI4CE 84 195 0 05 Feb 2022
Nested Graph Neural Networks Muhan Zhang Pan Li 78 167 0 25 Oct 2021
Equivariant Subgraph Aggregation Networks Beatrice Bevilacqua Fabrizio Frasca Derek Lim Balasubramaniam Srinivasan Chen Cai G. Balamurugan M. Bronstein Haggai Maron 101 179 0 06 Oct 2021
Scalars are universal: Equivariant machine learning, structured like classical physics Soledad Villar D. Hogg Kate Storey-Fisher Weichi Yao Ben Blum-Smith PINN AI4CE 61 135 0 11 Jun 2021
GemNet: Universal Directional Graph Neural Networks for Molecules Johannes Klicpera Florian Becker Stephan Günnemann AI4CE 86 457 0 02 Jun 2021
MLP-Mixer: An all-MLP Architecture for Vision Ilya O. Tolstikhin N. Houlsby Alexander Kolesnikov Lucas Beyer Xiaohua Zhai ... Andreas Steiner Daniel Keysers Jakob Uszkoreit Mario Lucic Alexey Dosovitskiy 411 2,673 0 04 May 2021
E(n) Equivariant Graph Neural Networks Victor Garcia Satorras Emiel Hoogeboom Max Welling 102 1,020 0 19 Feb 2021
Topological Graph Neural Networks Max Horn E. Brouwer Michael Moor Yves Moreau Bastian Rieck Karsten Borgwardt AI4CE 57 95 0 15 Feb 2021
Equivariant message passing for the prediction of tensorial properties and molecular spectra Kristof T. Schütt Oliver T. Unke M. Gastegger 104 531 0 05 Feb 2021
Fast and Uncertainty-Aware Directional Message Passing for Non-Equilibrium Molecules Johannes Klicpera Shankari Giri Johannes T. Margraf Stephan Günnemann 79 322 0 28 Nov 2020
On the Universality of Rotation Equivariant Point Cloud Networks Nadav Dym Haggai Maron 3DPC 85 83 0 06 Oct 2020
SE(3)-Transformers: 3D Roto-Translation Equivariant Attention Networks F. Fuchs Daniel E. Worrall Volker Fischer Max Welling 3DPC 151 692 0 18 Jun 2020
Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting Giorgos Bouritsas Fabrizio Frasca Stefanos Zafeiriou M. Bronstein 116 430 0 16 Jun 2020
Directional Message Passing for Molecular Graphs Johannes Klicpera Janek Groß Stephan Günnemann 122 871 0 06 Mar 2020
Learning to Simulate Complex Physics with Graph Networks Alvaro Sanchez-Gonzalez Jonathan Godwin Tobias Pfaff Rex Ying J. Leskovec Peter W. Battaglia PINN AI4CE 136 1,089 0 21 Feb 2020
Generalization and Representational Limits of Graph Neural Networks Vikas Garg Stefanie Jegelka Tommi Jaakkola GNN 94 313 0 14 Feb 2020
Deep Learning for 3D Point Clouds: A Survey Yulan Guo Hanyun Wang Qingyong Hu Hao Liu Li Liu Bennamoun 3DPC 91 1,674 0 27 Dec 2019
Cormorant: Covariant Molecular Neural Networks Brandon M. Anderson Truong-Son Hy Risi Kondor 93 425 0 06 Jun 2019
On the equivalence between graph isomorphism testing and function approximation with GNNs Zhengdao Chen Soledad Villar Lei Chen Joan Bruna 81 281 0 29 May 2019
Provably Powerful Graph Networks Haggai Maron Heli Ben-Hamu Hadar Serviansky Y. Lipman 118 579 0 27 May 2019
Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks Christopher Morris Martin Ritzert Matthias Fey William L. Hamilton J. E. Lenssen Gaurav Rattan Martin Grohe GNN 192 1,634 0 04 Oct 2018
How Powerful are Graph Neural Networks? Keyulu Xu Weihua Hu J. Leskovec Stefanie Jegelka GNN 238 7,642 0 01 Oct 2018
Tensor field networks: Rotation- and translation-equivariant neural networks for 3D point clouds Nathaniel Thomas Tess E. Smidt S. Kearnes Lusann Yang Li Li Kai Kohlhoff Patrick F. Riley 3DPC 83 970 0 22 Feb 2018
Neural Message Passing for Quantum Chemistry Justin Gilmer S. Schoenholz Patrick F. Riley Oriol Vinyals George E. Dahl 590 7,443 0 04 Apr 2017
MoleculeNet: A Benchmark for Molecular Machine Learning Zhenqin Wu Bharath Ramsundar Evan N. Feinberg Joseph Gomes C. Geniesse Aneesh S. Pappu K. Leswing Vijay S. Pande OOD 332 1,827 0 02 Mar 2017