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
Canonical Fields: Self-Supervised Learning of Pose-Canonicalized Neural Fields Rohith Agaram Shaurya Dewan Rahul Sajnani A. Poulenard Madhava Krishna Srinath Sridhar 36 6 0 05 Dec 2022
Equivalence Between SE(3) Equivariant Networks via Steerable Kernels and Group Convolution A. Poulenard M. Ovsjanikov Leonidas J. Guibas 3DPC 32 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 23 2 0 26 Nov 2022
Neural DAEs: Constrained neural networks Tue Boesen E. Haber Uri M. Ascher 39 3 0 25 Nov 2022
PAC-Bayes Compression Bounds So Tight That They Can Explain Generalization Sanae Lotfi Marc Finzi Sanyam Kapoor Andres Potapczynski Micah Goldblum A. Wilson BDL MLT AI4CE 29 51 0 24 Nov 2022
Equivariant Networks for Crystal Structures Sekouba Kaba Siamak Ravanbakhsh AI4CE 48 23 0 15 Nov 2022
Equivariance with Learned Canonicalization Functions Sekouba Kaba Arnab Kumar Mondal Yan Zhang Yoshua Bengio Siamak Ravanbakhsh 44 62 0 11 Nov 2022
Gauge Equivariant Neural Networks for 2+1D U(1) Gauge Theory Simulations in Hamiltonian Formulation Di Luo Shunyue Yuan J. Stokes B. Clark 21 14 0 06 Nov 2022
Learning the shape of protein micro-environments with a holographic convolutional neural network Michael N. Pun Andrew Ivanov Quinn Bellamy Zachary Montague Colin H. LaMont P. Bradley J. Otwinowski Armita Nourmohammad 19 12 0 05 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 38 19 0 31 Oct 2022
Transferable E(3) equivariant parameterization for Hamiltonian of molecules and solids Yang Zhong Hongyu Yu Mao Su X. Gong H. Xiang 36 36 0 28 Oct 2022
A PAC-Bayesian Generalization Bound for Equivariant Networks Arash Behboodi Gabriele Cesa Taco S. Cohen 56 17 0 24 Oct 2022
Theoretical Guarantees for Permutation-Equivariant Quantum Neural Networks Louis Schatzki Martín Larocca Quynh T. Nguyen F. Sauvage M. Cerezo 39 84 0 18 Oct 2022
Theory for Equivariant Quantum Neural Networks Quynh T. Nguyen Louis Schatzki Paolo Braccia Michael Ragone Patrick J. Coles F. Sauvage Martín Larocca M. Cerezo 40 89 0 16 Oct 2022
Injecting Domain Knowledge from Empirical Interatomic Potentials to Neural Networks for Predicting Material Properties Zeren Shui Daniel S. Karls Mingjian Wen Ilia Nikiforov E. Tadmor George Karypis 46 7 0 14 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 36 31 0 14 Oct 2022
Forces are not Enough: Benchmark and Critical Evaluation for Machine Learning Force Fields with Molecular Simulations Xiang Fu Zhenghao Wu Wujie Wang T. Xie S. Keten Rafael Gómez-Bombarelli Tommi Jaakkola 32 136 0 13 Oct 2022
Learning Physical Dynamics with Subequivariant Graph Neural Networks Jiaqi Han Wenbing Huang Hengbo Ma Jiachen Li J. Tenenbaum Chuang Gan AI4CE PINN 40 43 0 13 Oct 2022
Guaranteed Conservation of Momentum for Learning Particle-based Fluid Dynamics L. Prantl Benjamin Ummenhofer V. Koltun Nils Thuerey AI4CE PINN 26 29 0 12 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
DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking Gabriele Corso Hannes Stärk Bowen Jing Regina Barzilay Tommi Jaakkola DiffM 142 412 0 04 Oct 2022
In Search of Projectively Equivariant Networks Georg Bökman Axel Flinth Fredrik Kahl 44 0 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
Exact conservation laws for neural network integrators of dynamical systems E. Müller PINN 41 12 0 23 Sep 2022
SELTO: Sample-Efficient Learned Topology Optimization Sören Dittmer David Erzmann Henrik Harms Peter Maass 32 2 0 12 Sep 2022
Bispectral Neural Networks Sophia Sanborn Christian Shewmake Bruno A. Olshausen Christopher Hillar 35 12 0 07 Sep 2022
Algorithmic Differentiation for Automated Modeling of Machine Learned Force Fields Niklas Schmitz Klaus-Robert Muller Stefan Chmiela AI4CE 21 11 0 25 Aug 2022
Graph neural networks for materials science and chemistry Patrick Reiser Marlen Neubert André Eberhard Luca Torresi Chen Zhou ... Houssam Metni Clint van Hoesel Henrik Schopmans T. Sommer Pascal Friederich GNN AI4CE 50 373 0 05 Aug 2022
e3nn: Euclidean Neural Networks Mario Geiger Tess E. Smidt 46 173 0 18 Jul 2022
$Image to Icosahedral Projection for $\mathrm{SO}(3)$ Object Reasoning from Single-View Images$ Image to Icosahedral Projection for $\mathrm{SO}(3)$ Object Reasoning from Single-View Images David M. Klee Ondrej Biza Robert W. Platt Robin Walters 26 4 0 18 Jul 2022
Pure Transformers are Powerful Graph Learners Jinwoo Kim Tien Dat Nguyen Seonwoo Min Sungjun Cho Moontae Lee Honglak Lee Seunghoon Hong 43 189 0 06 Jul 2022
Edge Direction-invariant Graph Neural Networks for Molecular Dipole Moments Prediction Yang Jeong Park GNN 23 1 0 26 Jun 2022
Maximum Class Separation as Inductive Bias in One Matrix Tejaswi Kasarla Gertjan J. Burghouts Max van Spengler Elise van der Pol Rita Cucchiara Pascal Mettes 26 22 0 17 Jun 2022
ComENet: Towards Complete and Efficient Message Passing for 3D Molecular Graphs Limei Wang Yi Liu Yu-Ching Lin Hao Liu Shuiwang Ji GNN 41 89 0 17 Jun 2022
Unified Fourier-based Kernel and Nonlinearity Design for Equivariant Networks on Homogeneous Spaces Yinshuang Xu Jiahui Lei Yan Sun Kostas Daniilidis 23 19 0 16 Jun 2022
Equivariant Descriptor Fields: SE(3)-Equivariant Energy-Based Models for End-to-End Visual Robotic Manipulation Learning Hyunwoo Ryu Jeong-Hoon Lee Honglak Lee Jongeun Choi 37 53 0 16 Jun 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 47 442 0 15 Jun 2022
E2PN: Efficient SE(3)-Equivariant Point Network Minghan Zhu Maani Ghaffari W. A. Clark Huei Peng 3DPC 27 18 0 11 Jun 2022
VN-Transformer: Rotation-Equivariant Attention for Vector Neurons Serge Assaad Carlton Downey Rami Al-Rfou Nigamaa Nayakanti Benjamin Sapp 36 18 0 08 Jun 2022
Utility of Equivariant Message Passing in Cortical Mesh Segmentation Dániel Unyi F. Insalata Petar Velickovic Bálint Gyires-Tóth 22 0 0 07 Jun 2022
Torsional Diffusion for Molecular Conformer Generation Bowen Jing Gabriele Corso Jeffrey Chang Regina Barzilay Tommi Jaakkola DiffM BDL 29 259 0 01 Jun 2022
3DLinker: An E(3) Equivariant Variational Autoencoder for Molecular Linker Design Yinan Huang Xing Peng Jianzhu Ma Muhan Zhang BDL 30 47 0 15 May 2022
Discovering and Explaining the Representation Bottleneck of Graph Neural Networks from Multi-order Interactions Fang Wu Siyuan Li Lirong Wu Dragomir R. Radev Stan Z. Li 27 2 0 15 May 2022
Pocket2Mol: Efficient Molecular Sampling Based on 3D Protein Pockets Xingang Peng Shitong Luo Jiaqi Guan Qi Xie Jian-wei Peng Jianzhu Ma 27 176 0 15 May 2022
Low Dimensional Invariant Embeddings for Universal Geometric Learning Nadav Dym S. Gortler 29 39 0 05 May 2022
DiffMD: A Geometric Diffusion Model for Molecular Dynamics Simulations Fang Wu Stan Z. Li DiffM 29 31 0 19 Apr 2022
SE(3)-Equivariant Attention Networks for Shape Reconstruction in Function Space Evangelos Chatzipantazis Stefanos Pertigkiozoglou Yan Sun Kostas Daniilidis 3DPC 34 30 0 05 Apr 2022
Shape-Pose Disentanglement using SE(3)-equivariant Vector Neurons Oren Katzir Dani Lischinski Daniel Cohen-Or 3DPC 35 14 0 03 Apr 2022
Dimensionless machine learning: Imposing exact units equivariance Soledad Villar Weichi Yao D. Hogg Ben Blum-Smith Bianca Dumitrascu 16 26 0 02 Apr 2022
Path Development Network with Finite-dimensional Lie Group Representation Han Lou Siran Li Hao Ni 18 7 0 02 Apr 2022