On the Universality of Rotation Equivariant Point Cloud Networks

6 October 2020

Papers citing "On the Universality of Rotation Equivariant Point Cloud Networks"

50 / 59 papers shown

Title
Using Random Noise Equivariantly to Boost Graph Neural Networks Universally X. Wang Muhan Zhang 102 0 0 04 Feb 2025
Rethinking Addressing in Language Models via Contexualized Equivariant Positional Encoding Jiajun Zhu Peihao Wang Ruisi Cai Jason D. Lee Pan Li Z. Wang KELM 36 1 0 03 Jan 2025
Equivariant Graph Network Approximations of High-Degree Polynomials for Force Field Prediction Zhao Xu Haiyang Yu Montgomery Bohde Shuiwang Ji 40 0 0 06 Nov 2024
Are High-Degree Representations Really Unnecessary in Equivariant Graph Neural Networks? Jiacheng Cen Anyi Li Ning Lin Yuxiang Ren Zihe Wang Wenbing Huang 38 2 0 15 Oct 2024
Towards Stable, Globally Expressive Graph Representations with Laplacian Eigenvectors Junru Zhou Cai Zhou Xiyuan Wang Pan Li Muhan Zhang 35 0 0 13 Oct 2024
Revisiting Multi-Permutation Equivariance through the Lens of Irreducible Representations Yonatan Sverdlov Ido Springer Nadav Dym 32 2 0 09 Oct 2024
Decomposition of Equivariant Maps via Invariant Maps: Application to Universal Approximation under Symmetry Akiyoshi Sannai Yuuki Takai Matthieu Cordonnier 134 0 0 25 Sep 2024
Optimal Symmetries in Binary Classification Vishal S. Ngairangbam M. Spannowsky 21 1 0 16 Aug 2024
Foundations and Frontiers of Graph Learning Theory Yu Huang Min Zhou Menglin Yang Zhen Wang Muhan Zhang Jie Wang Hong Xie Hao Wang Defu Lian Enhong Chen AI4CE GNN 50 2 0 03 Jul 2024
On the Expressive Power of Sparse Geometric MPNNs Yonatan Sverdlov Nadav Dym 40 1 0 02 Jul 2024
Separation Power of Equivariant Neural Networks Marco Pacini Xiaowen Dong Bruno Lepri G. Santin 26 0 0 13 Jun 2024
DifAttack++: Query-Efficient Black-Box Adversarial Attack via Hierarchical Disentangled Feature Space in Cross-Domain Jun Liu Jiantao Zhou Jiandian Zeng Jinyu Tian Zheng Li 35 0 0 05 Jun 2024
Graph as Point Set Xiyuan Wang Pan Li Muhan Zhang GNN 3DPC PINN 35 4 0 05 May 2024
A Survey of Geometric Graph Neural Networks: Data Structures, Models and Applications Jiaqi Han Jiacheng Cen Liming Wu Zongzhao Li Xiangzhe Kong ... Zhewei Wei Deli Zhao Yu Rong Wenbing Huang Wenbing Huang AI4CE 32 20 0 01 Mar 2024
On the Completeness of Invariant Geometric Deep Learning Models Zian Li Xiyuan Wang Shijia Kang Muhan Zhang 31 2 0 07 Feb 2024
Weisfeiler Leman for Euclidean Equivariant Machine Learning Snir Hordan Tal Amir Nadav Dym 44 5 0 04 Feb 2024
Enabling Efficient Equivariant Operations in the Fourier Basis via Gaunt Tensor Products Shengjie Luo Tianlang Chen Aditi S. Krishnapriyan 25 19 0 18 Jan 2024
A Characterization Theorem for Equivariant Networks with Point-wise Activations Marco Pacini Xiaowen Dong Bruno Lepri G. Santin 36 2 0 17 Jan 2024
Expressive Sign Equivariant Networks for Spectral Geometric Learning Derek Lim Joshua Robinson Stefanie Jegelka Haggai Maron 63 16 0 04 Dec 2023
$Learning Polynomial Problems with $SL(2,\mathbb{R})$ Equivariance$ Learning Polynomial Problems with $SL(2,\mathbb{R})$ Equivariance Hannah Lawrence Mitchell Tong Harris 22 1 0 04 Dec 2023
Learning Symmetrization for Equivariance with Orbit Distance Minimization Tien Dat Nguyen Jinwoo Kim Hongseok Yang Seunghoon Hong 30 3 0 13 Nov 2023
Fast, Expressive SE $(n)$ Equivariant Networks through Weight-Sharing in Position-Orientation Space Erik J. Bekkers Sharvaree P. Vadgama Rob D. Hesselink P. A. V. D. Linden David W. Romero 13 24 0 04 Oct 2023
Symmetric Models for Visual Force Policy Learning Colin Kohler A. S. Srikanth Eshan Arora Robert W. Platt 22 7 0 28 Aug 2023
Explainable Equivariant Neural Networks for Particle Physics: PELICAN A. Bogatskiy Timothy Hoffman David W. Miller Jan T. Offermann Xiaoyang Liu 24 24 0 31 Jul 2023
StrainTensorNet: Predicting crystal structure elastic properties using SE(3)-equivariant graph neural networks T. Pakornchote A. Ektarawong Thiparat Chotibut 17 4 0 22 Jun 2023
Symmetry-Informed Geometric Representation for Molecules, Proteins, and Crystalline Materials Shengchao Liu Weitao Du Yanjing Li Zhuoxinran Li Zhiling Zheng ... Anima Anandkumar C. Borgs J. Chayes Hongyu Guo Jian Tang AI4CE 31 19 0 15 Jun 2023
A new perspective on building efficient and expressive 3D equivariant graph neural networks Weitao Du Yuanqi Du Limei Wang Dieqiao Feng Guifeng Wang Shuiwang Ji Carla P. Gomes Zhixin Ma AI4CE 17 33 0 07 Apr 2023
The Exact Sample Complexity Gain from Invariances for Kernel Regression B. Tahmasebi Stefanie Jegelka 28 17 0 24 Mar 2023
Ewald-based Long-Range Message Passing for Molecular Graphs Arthur Kosmala Johannes Gasteiger Nicholas Gao Stephan Günnemann 66 25 0 08 Mar 2023
AI for Science: An Emerging Agenda Philipp Berens Kyle Cranmer Neil D. Lawrence U. V. Luxburg Jessica Montgomery 24 4 0 07 Mar 2023
Is Distance Matrix Enough for Geometric Deep Learning? Zian Li Xiyuan Wang Yinan Huang Muhan Zhang 32 17 0 11 Feb 2023
Complete Neural Networks for Complete Euclidean Graphs Snir Hordan Tal Amir S. Gortler Nadav Dym 3DPC 19 5 0 31 Jan 2023
On the Expressive Power of Geometric Graph Neural Networks Chaitanya K. Joshi Cristian Bodnar Simon V. Mathis Taco Cohen Pietro Liò 45 83 0 23 Jan 2023
The Surprising Effectiveness of Equivariant Models in Domains with Latent Symmetry Dian Wang Jung Yeon Park Neel Sortur Lawson L. S. Wong Robin G. Walters Robert W. Platt AAML 25 33 0 16 Nov 2022
A tradeoff between universality of equivariant models and learnability of symmetries Vasco Portilheiro 25 2 0 17 Oct 2022
Machine learning and invariant theory Ben Blum-Smith Soledad Villar AI4CE 31 15 0 29 Sep 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 32 368 0 05 Aug 2022
Graph Neural Network with Local Frame for Molecular Potential Energy Surface Xiyuan Wang Muhan Zhang 25 8 0 01 Aug 2022
e3nn: Euclidean Neural Networks Mario Geiger Tess E. Smidt 24 173 0 18 Jul 2022
Unified Fourier-based Kernel and Nonlinearity Design for Equivariant Networks on Homogeneous Spaces Yinshuang Xu Jiahui Lei Edgar Dobriban Kostas Daniilidis 23 19 0 16 Jun 2022
VNT-Net: Rotational Invariant Vector Neuron Transformers Hedi Zisling Andrei Sharf 3DPC 16 1 0 19 May 2022
Low Dimensional Invariant Embeddings for Universal Geometric Learning Nadav Dym S. Gortler 21 39 0 05 May 2022
Learning Symmetric Embeddings for Equivariant World Models Jung Yeon Park Ondrej Biza Linfeng Zhao Jan Willem van de Meent Robin G. Walters 15 42 0 24 Apr 2022
A Simple and Universal Rotation Equivariant Point-cloud Network Ben Finkelshtein Chaim Baskin Haggai Maron Nadav Dym 3DPC 19 13 0 02 Mar 2022
Frame Averaging for Equivariant Shape Space Learning Matan Atzmon Koki Nagano Sanja Fidler S. Khamis Y. Lipman FedML 22 13 0 03 Dec 2021
ZZ-Net: A Universal Rotation Equivariant Architecture for 2D Point Clouds Georg Bökman Fredrik Kahl Axel Flinth 3DPC 21 19 0 30 Nov 2021
Directional Message Passing on Molecular Graphs via Synthetic Coordinates Johannes Klicpera Chandan Yeshwanth Stephan Günnemann 35 35 0 08 Nov 2021
Equivariant Deep Dynamical Model for Motion Prediction Bahar Azari Deniz Erdoğmuş 16 1 0 02 Nov 2021
SE(3) Equivariant Graph Neural Networks with Complete Local Frames Weitao Du He Zhang Yuanqi Du Qi Meng Wei-Neng Chen Bin Shao Tie-Yan Liu 48 78 0 26 Oct 2021
RPR-Net: A Point Cloud-based Rotation-aware Large Scale Place Recognition Network Zhaoxin Fan Zhenbo Song Wenping Zhang Hongyan Liu Jun He Xiaoyong Du 3DPC 16 9 0 29 Aug 2021