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Equivariant Graph Neural Networks (GNNs) that incorporate E(3) symmetry have achieved significant success in various scientific applications.
The reduction of a graph to canonical form and the algebra which appears therein
Boris Weisfeiler and Andrei Leman · 1968
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Quantum mechanics: non-relativistic theory
Lev Davidovich Landau and Evgenii Mikhailovich Lifshitz · 2013
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An introduction to numerical methods and analysis
James F Epperson · 2013
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Persistent homology analysis of protein structure, flexibility, and folding
Kelin Xia and Guo-Wei Wei · 2014
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Machine learning of accurate energy-conserving molecular force fields
Stefan Chmiela, Alexandre Tkatchenko, Huziel E Sauceda, Igor Poltavsky, Kristof T Schütt, and Klaus-Robert Müller · 2017
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Neural message passing for quantum chemistry
Justin Gilmer, Samuel S Schoenholz, Patrick F Riley, Oriol Vinyals, and George E Dahl · 2017
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Deep sets
Manzil Zaheer, Satwik Kottur, Siamak Ravanbakhsh, Barnabas Poczos, Russ R Salakhutdinov, and Alexander J Smola · 2017
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Tensor field networks: Rotation-and translation-equivariant neural networks for 3d point clouds
Nathaniel Thomas, Tess Smidt, Steven Kearnes, Lusann Yang, Li Li, Kai Kohlhoff, and Patrick Riley · 2018
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3d steerable cnns: Learning rotationally equivariant features in volumetric data
Maurice Weiler, Mario Geiger, Max Welling, Wouter Boomsma, and Taco S Cohen · 2018
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Introduction to quantum mechanics
David J Griffiths and Darrell F Schroeter · 2018
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Neural relational inference for interacting systems
Thomas Kipf, Ethan Fetaya, Kuan-Chieh Wang, Max Welling, and Richard Zemel · 2018
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Schnet–a deep learning architecture for molecules and materials
Kristof T Schütt, Huziel E Sauceda, P-J Kindermans, Alexandre Tkatchenko, and K-R Müller · 2018
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Equivariant flows: sampling configurations for multi-body systems with symmetric energies
Jonas Köhler, Leon Klein, and Frank Noé · 2019
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Atomic cluster expansion for accurate and transferable interatomic potentials
Ralf Drautz · 2019
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Se (3)-transformers: 3d roto-translation equivariant attention networks
Fabian Fuchs, Daniel Worrall, Volker Fischer, and Max Welling · 2020
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On the universality of rotation equivariant point cloud networks
Nadav Dym and Haggai Maron · 2020
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Learning from protein structure with geometric vector perceptrons
Bowen Jing, Stephan Eismann, Patricia Suriana, Raphael John Lamarre Townshend, and Ron Dror · 2020
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Directional message passing for molecular graphs
Johannes Klicpera, Janek Groß, and Stephan Günnemann · 2020
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SciPy 1.0: Fundamental Algorithms for Scientific Computing in Python
Pauli Virtanen, Ralf Gommers, Travis E. Oliphant, Matt Haberland, Tyler Reddy, David Cournapeau, Evgeni Burovski, Pearu Peterson, Warren Weckesser, Jonathan Bright, Stéfan J. van der Walt, Matthew Brett, Joshua Wilson, K. Jarrod Millman, Nikolay Mayorov, Andrew R. J. Nelson, Eric Jones, Robert Kern, Eric Larson, C J Carey, İlhan Polat, Yu Feng, Eric W. Moore, Jake VanderPlas, Denis Laxalde, Josef Perktold, Robert Cimrman, Ian Henriksen, E. A. Quintero, Charles R. Harris, Anne M. Archibald, Antônio H. Ribeiro, Fabian Pedregosa, Paul van Mulbregt, and SciPy 1.0 Contributors · 2020
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E(n) equivariant graph neural networks
Victor Garcia Satorras, Emiel Hoogeboom, and Max Welling · 2021
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Geometric deep learning: Grids, groups, graphs, geodesics, and gauges, 2021
Michael M. Bronstein, Joan Bruna, Taco Cohen, and Petar Veličković · 2021
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Frame averaging for invariant and equivariant network design
Omri Puny, Matan Atzmon, Edward J Smith, Ishan Misra, Aditya Grover, Heli Ben-Hamu, and Yaron Lipman · 2021
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Equivariant message passing for the prediction of tensorial properties and molecular spectra
Kristof Schütt, Oliver Unke, and Michael Gastegger · 2021
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Geometric and physical quantities improve e (3) equivariant message passing
Johannes Brandstetter, Rob Hesselink, Elise van der Pol, Erik J Bekkers, and Max Welling · 2021
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Gemnet: Universal directional graph neural networks for molecules
Johannes Gasteiger, Florian Becker, and Stephan Gunnemann · 2021
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Point group analysis in particle simulation data
Michael Engel · 2021
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Roto-translated local coordinate frames for interacting dynamical systems
Miltiadis Kofinas, Naveen Nagaraja, and Efstratios Gavves · 2021
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So3krates: Equivariant attention for interactions on arbitrary length-scales in molecular systems
Thorben Frank, Oliver Unke, and Klaus-Robert Müller · 2022
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Learning physical dynamics with subequivariant graph neural networks
Jiaqi Han, Wenbing Huang, Hengbo Ma, Jiachen Li, Josh Tenenbaum, and Chuang Gan · 2022
Cited alongside, same era.
Geodiff: A geometric diffusion model for molecular conformation generation
Minkai Xu, Lantao Yu, Yang Song, Chence Shi, Stefano Ermon, and Jian Tang · 2022
Cited alongside, same era.
E (3)-equivariant graph neural networks for data-efficient and accurate interatomic potentials
Simon Batzner, Albert Musaelian, Lixin Sun, Mario Geiger, Jonathan P Mailoa, Mordechai Kornbluth, Nicola Molinari, Tess E Smidt, and Boris Kozinsky · 2022
Cited alongside, same era.
Equivariant diffusion for molecule generation in 3d
Emiel Hoogeboom, Vıctor Garcia Satorras, Clément Vignac, and Max Welling · 2022
Cited alongside, same era.
Equivariant graph hierarchy-based neural networks
Jiaqi Han, Wenbing Huang, Tingyang Xu, and Yu Rong · 2022
Cited alongside, same era.
Better prior distribution for antibody design
Jun Wu, Xiangzhe Kong, Ningguan Sun, Jing Wei, Sisi Shan, Fuli Feng, Feng Wu, Jian Peng, Linqi Zhang, Yang Liu, et al · 2024
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Enhancing geometric representations for molecules with equivariant vector-scalar interactive message passing
Yusong Wang, Tong Wang, Shaoning Li, Xinheng He, Mingyu Li, Zun Wang, Nanning Zheng, Bin Shao, and Tie-Yan Liu · 2024
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Subequivariant reinforcement learning in 3d multi-entity physical environments
Runfa Chen, Ling Wang, Yu Du, Tianrui Xue, Fuchun Sun, Jianwei Zhang, and Wenbing Huang · 2024
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Equivariant spatio-temporal attentive graph networks to simulate physical dynamics
Liming Wu, Zhichao Hou, Jirui Yuan, Yu Rong, and Wenbing Huang · 2024
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Geometric trajectory diffusion models
Jiaqi Han, Minkai Xu, Aaron Lou, Haotian Ye, and Stefano Ermon · 2024
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Ilyes Batatia, David P Kovacs, Gregor Simm, Christoph Ortner, and Gábor Csányi · 2022
Cited alongside, same era.
e3nn: Euclidean neural networks
Mario Geiger and Tess Smidt · 2022
Cited alongside, same era.
Equivariant graph mechanics networks with constraints
Wenbing Huang, Jiaqi Han, Yu Rong, Tingyang Xu, Fuchun Sun, and Junzhou Huang · 2022
Cited alongside, same era.
Se (3) equivariant graph neural networks with complete local frames
Weitao Du, He Zhang, Yuanqi Du, Qi Meng, Wei Chen, Nanning Zheng, Bin Shao, and Tie-Yan Liu · 2022
Cited alongside, same era.
Comenet: Towards complete and efficient message passing for 3d molecular graphs
Limei Wang, Yi Liu, Yuchao Lin, Haoran Liu, and Shuiwang Ji · 2022
Cited alongside, same era.
Atomic cluster expansion: Completeness, efficiency and stability
Genevieve Dusson, Markus Bachmayr, Gábor Csányi, Ralf Drautz, Simon Etter, Cas van Der Oord, and Christoph Ortner · 2022
Cited alongside, same era.
Molecule generation by principal subgraph mining and assembling
Xiangzhe Kong, Wenbing Huang, Zhixing Tan, and Yang Liu · 2022
Cited alongside, same era.
Molcraft: Structure-based drug design in continuous parameter space
Yanru Qu, Keyue Qiu, Yuxuan Song, Jingjing Gong, Jiawei Han, Mingyue Zheng, Hao Zhou, and Wei-Ying Ma · 2024
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Rigid protein-protein docking via equivariant elliptic-paraboloid interface prediction
Ziyang Yu, Wenbing Huang, and Yang Liu · 2024
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Equivariant graph neural operator for modeling 3d dynamics
Minkai Xu, Jiaqi Han, Aaron Lou, Jean Kossaifi, Arvind Ramanathan, Kamyar Azizzadenesheli, Jure Leskovec, Stefano Ermon, and Anima Anandkumar · 2024
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Improving equivariant graph neural networks on large geometric graphs via virtual nodes learning
Yuelin Zhang, Jiacheng Cen, Jiaqi Han, Zhiqiang Zhang, Jun Zhou, and Wenbing Huang · 2024
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Neural p 3 m: A long-range interaction modeling enhancer for geometric gnns
Yusong Wang, Chaoran Cheng, Shaoning Li, Yuxuan Ren, Bin Shao, Ge Liu, Pheng-Ann Heng, and Nanning Zheng · 2024
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A survey of geometric graph neural networks: Data structures, models and applications
Jiaqi Han, Jiacheng Cen, Liming Wu, Zongzhao Li, Xiangzhe Kong, Rui Jiao, Ziyang Yu, Tingyang Xu, Fandi Wu, Zihe Wang, et al · 2024
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A euclidean transformer for fast and stable machine learned force fields
J Thorben Frank, Oliver T Unke, Klaus-Robert Müller, and Stefan Chmiela · 2024
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Improving equivariant networks with probabilistic symmetry breaking
Hannah Lawrence, Vasco Portilheiro, Yan Zhang, and Sékou-Oumar Kaba · 2024
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E (n) equivariant topological neural networks
Claudio Battiloro, Ege Karaismailoğlu, Mauricio Tec, George Dasoulas, Michelle Audirac, and Francesca Dominici · 2024
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Full-atom peptide design with geometric latent diffusion
Xiangzhe Kong, Wenbing Huang, and Yang Liu · 2024
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Equiformerv2: Improved equivariant transformer for scaling to higher-degree representations
Yi-Lun Liao, Brandon M Wood, Abhishek Das, and Tess Smidt · 2024
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Towards geometric normalization techniques in se(3) equivariant graph neural networks for physical dynamics simulations
Ziqiao Meng, Liang Zeng, Zixing Song, Tingyang Xu, Peilin Zhao, and Irwin King · 2024
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Is distance matrix enough for geometric deep learning?
Zian Li, Xiyuan Wang, Yinan Huang, and Muhan Zhang · 2024
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Bridging machine learning and thermodynamics for accurate p k a prediction
Weiliang Luo, Gengmo Zhou, Zhengdan Zhu, Yannan Yuan, Guolin Ke, Zhewei Wei, Zhifeng Gao, and Hang Zheng · 2024
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S-molsearch: 3d semi-supervised contrastive learning for bioactive molecule search
Gengmo Zhou, Zhen Wang, Feng Yu, Guolin Ke, Zhewei Wei, and Zhifeng Gao · 2024
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Mmpolymer: A multimodal multitask pretraining framework for polymer property prediction
Fanmeng Wang, Wentao Guo, Minjie Cheng, Shen Yuan, Hongteng Xu, and Zhifeng Gao · 2024
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A plug-and-play quaternion message-passing module for molecular conformation representation
Angxiao Yue, Dixin Luo, and Hongteng Xu · 2024
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Equipocket: an e (3)-equivariant geometric graph neural network for ligand binding site prediction
Yang Zhang, Wenbing Huang, Zhewei Wei, Ye Yuan, and Zhaohan Ding · 2024
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Force-guided bridge matching for full-atom time-coarsened dynamics of peptides
Ziyang Yu, Wenbing Huang, and Yang Liu · 2024
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Powder diffraction crystal structure determination using generative models
Qi Li, Rui Jiao, Liming Wu, Tiannian Zhu, Wenbing Huang, Shifeng Jin, Yang Liu, Hongming Weng, and Xiaolong Chen · 2024
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Crystal structure prediction by joint equivariant diffusion
Rui Jiao, Wenbing Huang, Peijia Lin, Jiaqi Han, Pin Chen, Yutong Lu, and Yang Liu · 2024
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3d structure prediction of atomic systems with flow-based direct preference optimization
Rui jiao, Xiangzhe Kong, Wenbing Huang, and Yang Liu · 2024
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