Tensor field networks: Rotation- and translation-equivariant neural networks for 3D point clouds

22 February 2018

Papers citing "Tensor field networks: Rotation- and translation-equivariant neural networks for 3D point clouds"

50 / 252 papers shown

Title
3D Equivariant Graph Implicit Functions Yunlu Chen Basura Fernando Hakan Bilen Matthias Nießner E. Gavves 3DPC 27 23 0 31 Mar 2022
When Physics Meets Machine Learning: A Survey of Physics-Informed Machine Learning Chuizheng Meng Sungyong Seo Defu Cao Sam Griesemer Yan Liu PINN AI4CE 44 57 0 31 Mar 2022
Equivariant Graph Mechanics Networks with Constraints Wen-bing Huang J. Han Yu Rong Tingyang Xu Gang Hua Junzhou Huang AI4CE 38 79 0 12 Mar 2022
Symmetry Group Equivariant Architectures for Physics A. Bogatskiy S. Ganguly Thomas Kipf Risi Kondor David W. Miller ... Jan T. Offermann M. Pettee P. Shanahan C. Shimmin S. Thais AI4CE 27 27 0 11 Mar 2022
GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generation Minkai Xu Lantao Yu Yang Song Chence Shi Stefano Ermon Jian Tang BDL DiffM 50 496 0 06 Mar 2022
A Simple and Universal Rotation Equivariant Point-cloud Network Ben Finkelshtein Chaim Baskin Haggai Maron Nadav Dym 3DPC 35 13 0 02 Mar 2022
Rotationally Equivariant Super-Resolution of Velocity Fields in Two-Dimensional Fluids Using Convolutional Neural Networks Y. Yasuda R. Onishi 25 5 0 22 Feb 2022
Equivariant Graph Attention Networks for Molecular Property Prediction Tuan Le Frank Noé Djork-Arné Clevert 16 21 0 20 Feb 2022
Unsupervised Learning of Group Invariant and Equivariant Representations R. Winter Marco Bertolini Tuan Le Frank Noé Djork-Arné Clevert 25 40 0 15 Feb 2022
EquiBind: Geometric Deep Learning for Drug Binding Structure Prediction Hannes Stärk O. Ganea L. Pattanaik Regina Barzilay Tommi Jaakkola 24 262 0 07 Feb 2022
Noether Networks: Meta-Learning Useful Conserved Quantities Ferran Alet Dylan D. Doblar Allan Zhou J. Tenenbaum Kenji Kawaguchi Chelsea Finn 73 26 0 06 Dec 2021
Frame Averaging for Equivariant Shape Space Learning Matan Atzmon Koki Nagano Sanja Fidler S. Khamis Y. Lipman FedML 33 13 0 03 Dec 2021
Equivariant graph neural networks for fast electron density estimation of molecules, liquids, and solids Peter Bjørn Jørgensen Arghya Bhowmik 16 36 0 01 Dec 2021
ZZ-Net: A Universal Rotation Equivariant Architecture for 2D Point Clouds Georg Bökman Fredrik Kahl Axel Flinth 3DPC 26 19 0 30 Nov 2021
Deformation Robust Roto-Scale-Translation Equivariant CNNs Liyao (Mars) Gao Guang Lin Wei-wei Zhu 22 8 0 22 Nov 2021
Independent SE(3)-Equivariant Models for End-to-End Rigid Protein Docking O. Ganea Xinyuan Huang Charlotte Bunne Yatao Bian Regina Barzilay Tommi Jaakkola Andreas Krause 36 151 0 15 Nov 2021
Self-Interpretable Model with TransformationEquivariant Interpretation Yipei Wang Xiaoqian Wang 38 23 0 09 Nov 2021
Directional Message Passing on Molecular Graphs via Synthetic Coordinates Johannes Klicpera Chandan Yeshwanth Stephan Günnemann 42 35 0 08 Nov 2021
Leveraging SE(3) Equivariance for Self-Supervised Category-Level Object Pose Estimation Xiaolong Li Yijia Weng Li Yi Leonidas J. Guibas A. L. Abbott Shuran Song He Wang 3DPC 44 53 0 30 Oct 2021
Roto-translated Local Coordinate Frames For Interacting Dynamical Systems Miltiadis Kofinas N. S. Nagaraja E. Gavves AI4CE 19 32 0 28 Oct 2021
SE(3) Equivariant Graph Neural Networks with Complete Local Frames Weitao Du He Zhang Yuanqi Du Qi Meng Wei Chen Bin Shao Tie-Yan Liu 56 79 0 26 Oct 2021
Surrogate- and invariance-boosted contrastive learning for data-scarce applications in science Charlotte Loh T. Christensen Rumen Dangovski Samuel Kim Marin Soljacic 32 16 0 15 Oct 2021
FlexConv: Continuous Kernel Convolutions with Differentiable Kernel Sizes David W. Romero Robert-Jan Bruintjes Jakub M. Tomczak Erik J. Bekkers Mark Hoogendoorn Jan van Gemert 80 82 0 15 Oct 2021
Relative Molecule Self-Attention Transformer Lukasz Maziarka Dawid Majchrowski Tomasz Danel Piotr Gaiñski Jacek Tabor Igor T. Podolak Pawel M. Morkisz Stanislaw Jastrzebski MedIm 40 34 0 12 Oct 2021
Ab-Initio Potential Energy Surfaces by Pairing GNNs with Neural Wave Functions Nicholas Gao Stephan Günnemann 27 36 0 11 Oct 2021
Multi-Agent MDP Homomorphic Networks Elise van der Pol H. V. Hoof F. Oliehoek Max Welling AI4CE 46 28 0 09 Oct 2021
Learning 3D Representations of Molecular Chirality with Invariance to Bond Rotations Keir Adams L. Pattanaik Connor W. Coley 21 32 0 08 Oct 2021
Geometric and Physical Quantities Improve E(3) Equivariant Message Passing Johannes Brandstetter Rob D. Hesselink Elise van der Pol Erik J. Bekkers Max Welling 17 229 0 06 Oct 2021
Top-N: Equivariant set and graph generation without exchangeability Clément Vignac P. Frossard BDL 71 34 0 05 Oct 2021
Molformer: Motif-based Transformer on 3D Heterogeneous Molecular Graphs Fang Wu Dragomir R. Radev Huabin Xing ViT 36 54 0 04 Oct 2021
Machine-learning hidden symmetries Ziming Liu Max Tegmark 48 52 0 20 Sep 2021
Nonlinearities in Steerable SO(2)-Equivariant CNNs Daniel Franzen Michael Wand 38 3 0 14 Sep 2021
You Only Hypothesize Once: Point Cloud Registration with Rotation-equivariant Descriptors Haiping Wang Yuan Liu Zhen Dong Wenping Wang 3DPC 27 124 0 01 Sep 2021
Geometric Deep Learning on Molecular Representations Kenneth Atz F. Grisoni G. Schneider AI4CE 34 287 0 26 Jul 2021
Particle Convolution for High Energy Physics C. Shimmin 19 15 0 05 Jul 2021
Data efficiency in graph networks through equivariance Francesco Farina E. Slade 26 1 0 25 Jun 2021
Rotation Invariant Graph Neural Networks using Spin Convolutions Muhammed Shuaibi Adeesh Kolluru Abhishek Das Aditya Grover Anuroop Sriram Zachary W. Ulissi C. L. Zitnick AI4CE 30 67 0 17 Jun 2021
Simple GNN Regularisation for 3D Molecular Property Prediction & Beyond Jonathan Godwin Michael Schaarschmidt Alex Gaunt Alvaro Sanchez-Gonzalez Yulia Rubanova Petar Velivcković J. Kirkpatrick Peter W. Battaglia 41 60 0 15 Jun 2021
Equivariant Networks for Pixelized Spheres Mehran Shakerinava Siamak Ravanbakhsh 3DPC 31 19 0 12 Jun 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 24 130 0 11 Jun 2021
Scale-invariant scale-channel networks: Deep networks that generalise to previously unseen scales Ylva Jansson T. Lindeberg 11 23 0 11 Jun 2021
BIGDML: Towards Exact Machine Learning Force Fields for Materials H. E. Sauceda Luis E Gálvez-González Stefan Chmiela L. O. Paz-Borbón K. Müller A. Tkatchenko AI4CE 32 47 0 08 Jun 2021
Integrating Expert ODEs into Neural ODEs: Pharmacology and Disease Progression Zhaozhi Qian W. Zame L. Fleuren Paul Elbers M. Schaar OOD 19 53 0 05 Jun 2021
DISCO: accurate Discrete Scale Convolutions Ivan Sosnovik A. Moskalev A. Smeulders 26 31 0 04 Jun 2021
GemNet: Universal Directional Graph Neural Networks for Molecules Johannes Klicpera Florian Becker Stephan Günnemann AI4CE 39 435 0 02 Jun 2021
E(n) Equivariant Normalizing Flows Victor Garcia Satorras Emiel Hoogeboom F. Fuchs Ingmar Posner Max Welling BDL 37 168 0 19 May 2021
Protein sequence-to-structure learning: Is this the end(-to-end revolution)? É. Laine Stephan Eismann A. Elofsson Sergei Grudinin OOD 3DV 23 34 0 16 May 2021
Learning Gradient Fields for Molecular Conformation Generation Chence Shi Shitong Luo Minkai Xu Jian Tang DiffM AI4CE 31 212 0 09 May 2021
SpookyNet: Learning Force Fields with Electronic Degrees of Freedom and Nonlocal Effects Oliver T. Unke Stefan Chmiela M. Gastegger Kristof T. Schütt H. E. Sauceda K. Müller 177 247 0 01 May 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 114 316 0 25 Apr 2021