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 / 251 papers shown

Title
A Practical Method for Constructing Equivariant Multilayer Perceptrons for Arbitrary Matrix Groups Marc Finzi Max Welling A. Wilson 79 185 0 19 Apr 2021
Field Convolutions for Surface CNNs Thomas W. Mitchel Vladimir G. Kim Michael Kazhdan 26 19 0 08 Apr 2021
Equivariant Point Network for 3D Point Cloud Analysis Haiwei Chen Shichen Liu Weikai Chen Hao Li 3DPC 19 99 0 25 Mar 2021
E(n) Equivariant Graph Neural Networks Victor Garcia Satorras Emiel Hoogeboom Max Welling 30 979 0 19 Feb 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 230 1,240 0 08 Jan 2021
LieTransformer: Equivariant self-attention for Lie Groups M. Hutchinson Charline Le Lan Sheheryar Zaidi Emilien Dupont Yee Whye Teh Hyunjik Kim 26 111 0 20 Dec 2020
Molecular machine learning with conformer ensembles Simon Axelrod Rafael Gómez-Bombarelli AI4CE 20 49 0 15 Dec 2020
Symmetry-Aware Actor-Critic for 3D Molecular Design G. Simm Robert Pinsler Gábor Csányi José Miguel Hernández-Lobato AI4CE 29 64 0 25 Nov 2020
Deep Positional and Relational Feature Learning for Rotation-Invariant Point Cloud Analysis Ruixuan Yu Xin Wei Federico Tombari Jian Sun 3DPC 27 37 0 18 Nov 2020
Spherical convolutions on molecular graphs for protein model quality assessment Ilia Igashov Nikita Pavlichenko Sergei Grudinin 24 14 0 16 Nov 2020
Machine learning of solvent effects on molecular spectra and reactions M. Gastegger Kristof T. Schütt Klaus-Robert Muller AI4CE 17 59 0 28 Oct 2020
Trajectory Prediction using Equivariant Continuous Convolution Robin Walters Jinxi Li Rose Yu 26 43 0 21 Oct 2020
A Wigner-Eckart Theorem for Group Equivariant Convolution Kernels Leon Lang Maurice Weiler 35 53 0 21 Oct 2020
Probabilistic Numeric Convolutional Neural Networks Marc Finzi Roberto Bondesan Max Welling BDL AI4TS 29 13 0 21 Oct 2020
On the Universality of Rotation Equivariant Point Cloud Networks Nadav Dym Haggai Maron 3DPC 35 78 0 06 Oct 2020
RISA-Net: Rotation-Invariant Structure-Aware Network for Fine-Grained 3D Shape Retrieval Rao Fu Jie Yang Jiawei Sun Fang-Lue Zhang Yu-Kun Lai Lin Gao 3DV 3DPC 3DH 34 2 0 02 Oct 2020
Heterogeneous Molecular Graph Neural Networks for Predicting Molecule Properties Zeren Shui George Karypis 29 62 0 26 Sep 2020
Kohn-Sham equations as regularizer: building prior knowledge into machine-learned physics Li Li Stephan Hoyer Ryan Pederson Ruoxi Sun E. D. Cubuk Patrick F. Riley K. Burke AI4CE 35 120 0 17 Sep 2020
Learning from Protein Structure with Geometric Vector Perceptrons Bowen Jing Stephan Eismann Patricia Suriana Raphael J. L. Townshend R. Dror GNN 3DV 25 471 0 03 Sep 2020
Relevance of Rotationally Equivariant Convolutions for Predicting Molecular Properties Benjamin Kurt Miller Mario Geiger Tess E. Smidt Frank Noé 16 75 0 19 Aug 2020
Spin-Weighted Spherical CNNs Carlos Esteves A. Makadia Kostas Daniilidis 30 69 0 18 Jun 2020
SE(3)-Transformers: 3D Roto-Translation Equivariant Attention Networks F. Fuchs Daniel E. Worrall Volker Fischer Max Welling 3DPC 45 666 0 18 Jun 2020
Lorentz Group Equivariant Neural Network for Particle Physics A. Bogatskiy Brandon M. Anderson Jan T. Offermann M. Roussi David W. Miller Risi Kondor AI4CE 29 136 0 08 Jun 2020
Info3D: Representation Learning on 3D Objects using Mutual Information Maximization and Contrastive Learning Aditya Sanghi 3DPC SSL 11 101 0 04 Jun 2020
CNNs on Surfaces using Rotation-Equivariant Features R. Wiersma E. Eisemann Klaus Hildebrandt 28 69 0 02 Jun 2020
Deep Learning and Knowledge-Based Methods for Computer Aided Molecular Design -- Toward a Unified Approach: State-of-the-Art and Future Directions Abdulelah S. Alshehri R. Gani Fengqi You AI4CE 30 83 0 18 May 2020
A deep neural network for molecular wave functions in quasi-atomic minimal basis representation M. Gastegger A. McSloy M. Luya Kristof T. Schütt R. Maurer 13 46 0 11 May 2020
Theoretical Aspects of Group Equivariant Neural Networks Carlos Esteves 24 41 0 10 Apr 2020
Gauge Equivariant Mesh CNNs: Anisotropic convolutions on geometric graphs P. D. Haan Maurice Weiler Taco S. Cohen Max Welling 102 127 0 11 Mar 2020
Directional Message Passing for Molecular Graphs Johannes Klicpera Janek Groß Stephan Günnemann 54 848 0 06 Mar 2020
Generalizing Convolutional Neural Networks for Equivariance to Lie Groups on Arbitrary Continuous Data Marc Finzi Samuel Stanton Pavel Izmailov A. Wilson 28 316 0 25 Feb 2020
Roto-Translation Equivariant Convolutional Networks: Application to Histopathology Image Analysis Maxime W. Lafarge Erik J. Bekkers J. Pluim R. Duits M. Veta MedIm 27 74 0 20 Feb 2020
On Learning Sets of Symmetric Elements Haggai Maron Or Litany Gal Chechik Ethan Fetaya 30 132 0 20 Feb 2020
Attentive Group Equivariant Convolutional Networks David W. Romero Erik J. Bekkers Jakub M. Tomczak Mark Hoogendoorn 22 89 0 07 Feb 2020
Quaternion Equivariant Capsule Networks for 3D Point Clouds Yongheng Zhao Tolga Birdal J. E. Lenssen Emanuele Menegatti Leonidas J. Guibas Federico Tombari 3DPC 26 88 0 27 Dec 2019
Geometry Sharing Network for 3D Point Cloud Classification and Segmentation Mingye Xu Zhipeng Zhou Yu Qiao 3DPC 21 92 0 23 Dec 2019
Representation Learning on Unit Ball with 3D Roto-Translational Equivariance Sameera Ramasinghe Salman Khan Nick Barnes Stephen Gould 13 8 0 30 Nov 2019
Deep Learning for 2D and 3D Rotatable Data: An Overview of Methods Luca Della Libera Vladimir Golkov Yue Zhu Arman Mielke Daniel Cremers 3DH 3DPC 25 4 0 31 Oct 2019
B-Spline CNNs on Lie Groups Erik J. Bekkers AI4CE 29 129 0 26 Sep 2019
Effective Rotation-invariant Point CNN with Spherical Harmonics kernels A. Poulenard Marie-Julie Rakotosaona Yann Ponty M. Ovsjanikov 3DPC 25 102 0 27 Jun 2019
Unifying machine learning and quantum chemistry -- a deep neural network for molecular wavefunctions Kristof T. Schütt M. Gastegger A. Tkatchenko K. Müller R. Maurer AI4CE 29 382 0 24 Jun 2019
Cormorant: Covariant Molecular Neural Networks Brandon M. Anderson Truong-Son Hy Risi Kondor 27 421 0 06 Jun 2019
Discrete Rotation Equivariance for Point Cloud Recognition Jiaxin Li Yingcai Bi Gim Hee Lee 3DPC 27 24 0 31 Mar 2019
Gauge Equivariant Convolutional Networks and the Icosahedral CNN Taco S. Cohen Maurice Weiler Berkay Kicanaoglu Max Welling 61 402 0 11 Feb 2019
Deep Learning on Attributed Graphs: A Journey from Graphs to Their Embeddings and Back M. Simonovsky BDL GNN 26 1 0 24 Jan 2019
3DTI-Net: Learn Inner Transform Invariant 3D Geometry Features using Dynamic GCN G. Pan Jun Wang R. Ying Peilin Liu 3DPC 9 16 0 15 Dec 2018
A General Theory of Equivariant CNNs on Homogeneous Spaces Taco S. Cohen Mario Geiger Maurice Weiler MLT AI4CE 165 308 0 05 Nov 2018
3D Steerable CNNs: Learning Rotationally Equivariant Features in Volumetric Data Maurice Weiler Mario Geiger Max Welling Wouter Boomsma Taco S. Cohen 3DPC 45 494 0 06 Jul 2018
Clebsch-Gordan Nets: a Fully Fourier Space Spherical Convolutional Neural Network Risi Kondor Zhen Lin Shubhendu Trivedi 42 264 0 24 Jun 2018
Intertwiners between Induced Representations (with Applications to the Theory of Equivariant Neural Networks) Taco S. Cohen Mario Geiger Maurice Weiler 33 46 0 28 Mar 2018