SE(3)-Transformers: 3D Roto-Translation Equivariant Attention Networks

18 June 2020

Papers citing "SE(3)-Transformers: 3D Roto-Translation Equivariant Attention Networks"

50 / 412 papers shown

Title
Sampled Transformer for Point Sets Shidi Li Christian J. Walder Alexander Soen Lexing Xie Miaomiao Liu 3DPC 10 1 0 28 Feb 2023
Self-Supervised Category-Level Articulated Object Pose Estimation with Part-Level SE(3) Equivariance Xueyi Liu Ji Zhang Ruizhen Hu Haibin Huang He-Nan Wang Li Yi 3DPC 16 21 0 28 Feb 2023
Image to Sphere: Learning Equivariant Features for Efficient Pose Prediction David M. Klee Ondrej Biza Robert W. Platt Robin G. Walters 21 17 0 27 Feb 2023
Boosting Convolutional Neural Networks' Protein Binding Site Prediction Capacity Using SE(3)-invariant transformers, Transfer Learning and Homology-based Augmentation Dae Lee Jeunghyun Byun Bonggun Shin OOD ViT 11 0 0 20 Feb 2023
Knowledge-augmented Graph Machine Learning for Drug Discovery: A Survey from Precision to Interpretability Zhiqiang Zhong A. Barkova Davide Mottin 14 8 0 16 Feb 2023
Transformer models: an introduction and catalog X. Amatriain Ananth Sankar Jie Bing Praveen Kumar Bodigutla Timothy J. Hazen Michaeel Kazi 19 50 0 12 Feb 2023
Is Distance Matrix Enough for Geometric Deep Learning? Zian Li Xiyuan Wang Yinan Huang Muhan Zhang 30 17 0 11 Feb 2023
Geometry-Complete Diffusion for 3D Molecule Generation and Optimization Alex Morehead Jianlin Cheng DiffM 14 22 0 08 Feb 2023
Attending to Graph Transformers Luis Muller Mikhail Galkin Christopher Morris Ladislav Rampášek 44 85 0 08 Feb 2023
Reducing SO(3) Convolutions to SO(2) for Efficient Equivariant GNNs Saro Passaro C. L. Zitnick 3DPC 14 78 0 07 Feb 2023
GPS++: Reviving the Art of Message Passing for Molecular Property Prediction Dominic Masters Josef Dean Kerstin Klaser Zhiyi Li Sam Maddrell-Mander ... D. Beker Andrew Fitzgibbon Shenyang Huang Ladislav Rampášek Dominique Beaini 28 8 0 06 Feb 2023
Molecular Geometry-aware Transformer for accurate 3D Atomic System modeling Zheng Yuan Yaoyun Zhang Chuanqi Tan Wei Wang Feiran Huang Songfang Huang AI4CE ViT 8 6 0 02 Feb 2023
End-to-End Full-Atom Antibody Design Xiangzhe Kong Wenbing Huang Yang Liu 11 48 0 01 Feb 2023
On the Expressive Power of Geometric Graph Neural Networks Chaitanya K. Joshi Cristian Bodnar Simon V. Mathis Taco Cohen Pietro Liò 42 82 0 23 Jan 2023
Spatial Attention Kinetic Networks with E(n)-Equivariance Yuanqing Wang J. Chodera 17 15 0 21 Jan 2023
Everything is Connected: Graph Neural Networks Petar Velickovic GNN AI4CE 20 178 0 19 Jan 2023
Heterogeneous Multi-Robot Reinforcement Learning Matteo Bettini Ajay Shankar Amanda Prorok 17 39 0 17 Jan 2023
Equivariant Light Field Convolution and Transformer Yinshuang Xu Jiahui Lei Kostas Daniilidis ViT 12 0 0 30 Dec 2022
INO: Invariant Neural Operators for Learning Complex Physical Systems with Momentum Conservation Ning Liu Yue Yu Huaiqian You Neeraj Tatikola AI4CE 11 23 0 29 Dec 2022
Implicit Convolutional Kernels for Steerable CNNs Maksim Zhdanov Nico Hoffmann Gabriele Cesa 19 5 0 12 Dec 2022
Canonical Fields: Self-Supervised Learning of Pose-Canonicalized Neural Fields Rohith Agaram Shaurya Dewan Rahul Sajnani A. Poulenard Madhava Krishna Srinath Sridhar 28 6 0 05 Dec 2022
Protein Language Models and Structure Prediction: Connection and Progression Bozhen Hu Jun-Xiong Xia Jiangbin Zheng Cheng Tan Yufei Huang Yongjie Xu Stan Z. Li 19 40 0 30 Nov 2022
Equivalence Between SE(3) Equivariant Networks via Steerable Kernels and Group Convolution A. Poulenard M. Ovsjanikov Leonidas J. Guibas 3DPC 22 2 0 29 Nov 2022
TetraSphere: A Neural Descriptor for O(3)-Invariant Point Cloud Analysis Pavlo Melnyk Andreas Robinson M. Felsberg Maarten Wadenback 3DPC 16 2 0 26 Nov 2022
A Self-Attention Ansatz for Ab-initio Quantum Chemistry Ingrid von Glehn J. Spencer David Pfau 19 60 0 24 Nov 2022
Learning Regularized Positional Encoding for Molecular Prediction Xiang Gao Weihao Gao Wen Xiao Zhirui Wang Chong Wang Liang Xiang AI4CE 14 1 0 23 Nov 2022
PhAST: Physics-Aware, Scalable, and Task-specific GNNs for Accelerated Catalyst Design Alexandre Duval Victor Schmidt Santiago Miret Yoshua Bengio Alex Hernández-García David Rolnick 22 7 0 22 Nov 2022
Equivariance with Learned Canonicalization Functions Sekouba Kaba Arnab Kumar Mondal Yan Zhang Yoshua Bengio Siamak Ravanbakhsh 23 61 0 11 Nov 2022
Rotation-equivariant Graph Neural Networks for Learning Glassy Liquids Representations F. Pezzicoli Guillaume Charpiat François P. Landes 8 6 0 06 Nov 2022
Geometry-Complete Perceptron Networks for 3D Molecular Graphs Alex Morehead Jianlin Cheng GNN 3DV AI4CE 19 12 0 04 Nov 2022
The Open MatSci ML Toolkit: A Flexible Framework for Machine Learning in Materials Science Santiago Miret Kin Long Kelvin Lee Carmelo Gonzales Marcel Nassar Matthew Spellings 27 19 0 31 Oct 2022
Interpretable Geometric Deep Learning via Learnable Randomness Injection Siqi Miao Yunan Luo Miaoyuan Liu Pan Li 11 24 0 30 Oct 2022
Breaking the Symmetry: Resolving Symmetry Ambiguities in Equivariant Neural Networks S. Balachandar A. Poulenard Congyue Deng Leonidas J. Guibas 12 1 0 29 Oct 2022
Continual Vision-based Reinforcement Learning with Group Symmetries Shiqi Liu Mengdi Xu Piede Huang Yongkang Liu K. Oguchi Ding Zhao CLL VLM 40 10 0 21 Oct 2022
PEMP: Leveraging Physics Properties to Enhance Molecular Property Prediction Yuancheng Sun Yimeng Chen Weizhi Ma Wenhao Huang Kang Liu Zhiming Ma Wei-Ying Ma Yanyan Lan 10 7 0 18 Oct 2022
Frame Mining: a Free Lunch for Learning Robotic Manipulation from 3D Point Clouds Minghua Liu Xuanlin Li Z. Ling Yangyan Li Hao Su 29 31 0 14 Oct 2022
Learning Physical Dynamics with Subequivariant Graph Neural Networks Jiaqi Han Wenbing Huang Hengbo Ma Jiachen Li J. Tenenbaum Chuang Gan AI4CE PINN 27 43 0 13 Oct 2022
Equi-Tuning: Group Equivariant Fine-Tuning of Pretrained Models Sourya Basu P. Sattigeri K. Ramamurthy Vijil Chenthamarakshan Kush R. Varshney L. Varshney Payel Das 8 18 0 13 Oct 2022
Why self-attention is Natural for Sequence-to-Sequence Problems? A Perspective from Symmetries Chao Ma Lexing Ying 17 2 0 13 Oct 2022
In What Ways Are Deep Neural Networks Invariant and How Should We Measure This? Henry Kvinge Tegan H. Emerson Grayson Jorgenson Scott Vasquez T. Doster Jesse D. Lew 35 8 0 07 Oct 2022
Equivariant Shape-Conditioned Generation of 3D Molecules for Ligand-Based Drug Design Keir Adams Connor W. Coley 34 25 0 06 Oct 2022
Coarse-to-Fine Point Cloud Registration with SE(3)-Equivariant Representations Chengxuan Lin Tung-I Chen Hsin-Ying Lee Wen-Chin Chen Winston H. Hsu 3DPC 8 11 0 05 Oct 2022
Holographic-(V)AE: an end-to-end SO(3)-Equivariant (Variational) Autoencoder in Fourier Space Gian Marco Visani Michael N. Pun Arman Angaji Armita Nourmohammad BDL 19 3 0 30 Sep 2022
Equivariant Energy-Guided SDE for Inverse Molecular Design Fan Bao Min Zhao Zhongkai Hao Pei‐Yun Li Chongxuan Li Jun Zhu DiffM 179 63 0 30 Sep 2022
Improving Molecular Pretraining with Complementary Featurizations Yanqiao Zhu Dingshuo Chen Yuanqi Du Yingze Wang Qiang Liu Shu Wu AI4CE 28 6 0 29 Sep 2022
Machine learning and invariant theory Ben Blum-Smith Soledad Villar AI4CE 23 15 0 29 Sep 2022
A Simple Strategy to Provable Invariance via Orbit Mapping Kanchana Vaishnavi Gandikota Jonas Geiping Zorah Lähner Adam Czapliñski Michael Moeller AAML 3DPC 18 3 0 24 Sep 2022
Periodic Graph Transformers for Crystal Material Property Prediction Keqiang Yan Yi Liu Yu-Ching Lin Shuiwang Ji AI4TS 88 84 0 23 Sep 2022
Deep learning for reconstructing protein structures from cryo-EM density maps: recent advances and future directions Nabin Giri Rajashree Roy Jianlin Cheng 3DV 14 40 0 16 Sep 2022
SVNet: Where SO(3) Equivariance Meets Binarization on Point Cloud Representation Z. Su Max Welling M. Pietikäinen Li Liu 3DPC 22 11 0 13 Sep 2022