On the Generalization of Equivariance and Convolution in Neural Networks to the Action of Compact Groups

11 February 2018

Papers citing "On the Generalization of Equivariance and Convolution in Neural Networks to the Action of Compact Groups"

50 / 320 papers shown

Title
Equivariance versus Augmentation for Spherical Images Jan E. Gerken Oscar Carlsson H. Linander F. Ohlsson Christoffer Petersson Daniel Persson 3DPC 20 14 0 08 Feb 2022
Data-driven emergence of convolutional structure in neural networks Alessandro Ingrosso Sebastian Goldt 48 38 0 01 Feb 2022
Equivariant neural networks for recovery of Hadamard matrices A. Peres E. Dias Luís Sarmento Hugo Penedones 8 0 0 31 Jan 2022
Approximately Equivariant Networks for Imperfectly Symmetric Dynamics Rui Wang Robin G. Walters Rose Yu 29 73 0 28 Jan 2022
Scientific Machine Learning through Physics-Informed Neural Networks: Where we are and What's next S. Cuomo Vincenzo Schiano Di Cola F. Giampaolo G. Rozza Maizar Raissi F. Piccialli PINN 24 1,177 0 14 Jan 2022
Set Twister for Single-hop Node Classification Yangze Zhou Vinayak A. Rao Bruno Ribeiro 25 0 0 17 Dec 2021
Speeding up Learning Quantum States through Group Equivariant Convolutional Quantum Ansätze Han Zheng Zimu Li Junyu Liu Sergii Strelchuk Risi Kondor 45 54 0 14 Dec 2021
Co-domain Symmetry for Complex-Valued Deep Learning Utkarsh Singhal Yifei Xing Stella X. Yu 23 12 0 02 Dec 2021
Rotation Equivariant 3D Hand Mesh Generation from a Single RGB Image Joshua Mitton Chaitanya Kaul Roderick Murray-Smith 3DH 18 0 0 25 Nov 2021
Quantised Transforming Auto-Encoders: Achieving Equivariance to Arbitrary Transformations in Deep Networks Jianbo Jiao João F. Henriques BDL OOD MQ 13 2 0 25 Nov 2021
Robust Equivariant Imaging: a fully unsupervised framework for learning to image from noisy and partial measurements Dongdong Chen Julián Tachella Mike E. Davies OOD 17 59 0 25 Nov 2021
ChebLieNet: Invariant Spectral Graph NNs Turned Equivariant by Riemannian Geometry on Lie Groups Hugo Aguettaz Erik J. Bekkers M. Defferrard GNN 9 1 0 23 Nov 2021
Enabling equivariance for arbitrary Lie groups L. MacDonald Sameera Ramasinghe Simon Lucey AAML 19 25 0 16 Nov 2021
Equivariant Deep Dynamical Model for Motion Prediction Bahar Azari Deniz Erdoğmuş 25 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 79 0 26 Oct 2021
Capacity of Group-invariant Linear Readouts from Equivariant Representations: How Many Objects can be Linearly Classified Under All Possible Views? M. Farrell Blake Bordelon Shubhendu Trivedi C. Pehlevan 13 5 0 14 Oct 2021
Implicit Bias of Linear Equivariant Networks Hannah Lawrence Kristian Georgiev A. Dienes B. Kiani AI4CE 32 14 0 12 Oct 2021
Ab-Initio Potential Energy Surfaces by Pairing GNNs with Neural Wave Functions Nicholas Gao Stephan Günnemann 19 36 0 11 Oct 2021
Equivariant Subgraph Aggregation Networks Beatrice Bevilacqua Fabrizio Frasca Derek Lim Balasubramaniam Srinivasan Chen Cai G. Balamurugan M. Bronstein Haggai Maron 46 174 0 06 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
Turing approximations, toric isometric embeddings & manifold convolutions P. Suárez-Serrato 18 1 0 05 Oct 2021
Top-N: Equivariant set and graph generation without exchangeability Clément Vignac P. Frossard BDL 63 34 0 05 Oct 2021
CLIPort: What and Where Pathways for Robotic Manipulation Mohit Shridhar Lucas Manuelli D. Fox LM&Ro 36 629 0 24 Sep 2021
Quantum algorithms for group convolution, cross-correlation, and equivariant transformations Grecia Castelazo Quynh T. Nguyen Giacomo De Palma Dirk Englund S. Lloyd B. Kiani 32 11 0 23 Sep 2021
Multi-Task Learning with Sequence-Conditioned Transporter Networks M. H. Lim Andy Zeng Brian Ichter Maryam Bandari Erwin Coumans Claire Tomlin S. Schaal Aleksandra Faust 30 14 0 15 Sep 2021
Automatic Symmetry Discovery with Lie Algebra Convolutional Network Nima Dehmamy Robin G. Walters Yanchen Liu Dashun Wang Rose Yu AI4CE 78 81 0 15 Sep 2021
Is Attention Better Than Matrix Decomposition? Zhengyang Geng Meng-Hao Guo Hongxu Chen Xia Li Ke Wei Zhouchen Lin 54 137 0 09 Sep 2021
Learning to Discover Reflection Symmetry via Polar Matching Convolution Ahyun Seo Woohyeon Shim Minsu Cho SSL 11 8 0 30 Aug 2021
Internal Video Inpainting by Implicit Long-range Propagation Hao Ouyang Tengfei Wang Qifeng Chen 29 36 0 04 Aug 2021
Fourier Series Expansion Based Filter Parametrization for Equivariant Convolutions Qi Xie Qian Zhao Zongben Xu Deyu Meng 11 19 0 30 Jul 2021
Circular-Symmetric Correlation Layer based on FFT Bahar Azari Deniz Erdogmus 34 1 0 26 Jul 2021
Geometric Deep Learning on Molecular Representations Kenneth Atz F. Grisoni G. Schneider AI4CE 30 286 0 26 Jul 2021
Transporting Causal Mechanisms for Unsupervised Domain Adaptation Zhongqi Yue Qianru Sun Xiansheng Hua Hanwang Zhang CML 17 56 0 23 Jul 2021
Correspondence-Free Point Cloud Registration with SO(3)-Equivariant Implicit Shape Representations Minghan Zhu Maani Ghaffari H. Peng 3DPC 27 36 0 21 Jul 2021
A Bayesian Approach to Invariant Deep Neural Networks Nikolaos Mourdoukoutas Marco Federici G. Pantalos Mark van der Wilk Vincent Fortuin BDL UQCV 21 0 0 20 Jul 2021
Equivariant Manifold Flows Isay Katsman Aaron Lou Derek Lim Qingxuan Jiang Ser-Nam Lim Christopher De Sa AI4CE 17 24 0 19 Jul 2021
Universal approximation and model compression for radial neural networks I. Ganev Twan van Laarhoven Robin G. Walters 19 8 0 06 Jul 2021
Physics-Guided Deep Learning for Dynamical Systems: A Survey Rui Wang Rose Yu AI4CE PINN 37 64 0 02 Jul 2021
Lossy Compression for Lossless Prediction Yann Dubois Benjamin Bloem-Reddy Karen Ullrich Chris J. Maddison 18 59 0 21 Jun 2021
Steerable Partial Differential Operators for Equivariant Neural Networks Erik Jenner Maurice Weiler 15 27 0 18 Jun 2021
Locality defeats the curse of dimensionality in convolutional teacher-student scenarios Alessandro Favero Francesco Cagnetta M. Wyart 22 31 0 16 Jun 2021
Category Theory in Machine Learning Dan Shiebler Bruno Gavranović Paul W. Wilson 13 31 0 13 Jun 2021
Equivariant Networks for Pixelized Spheres Mehran Shakerinava Siamak Ravanbakhsh 3DPC 23 19 0 12 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
Encoding Involutory Invariances in Neural Networks Anwesh Bhattacharya M. Mattheakis P. Protopapas 19 1 0 07 Jun 2021
VolterraNet: A higher order convolutional network with group equivariance for homogeneous manifolds Monami Banerjee Rudrasis Chakraborty Jose J. Bouza B. Vemuri 28 11 0 05 Jun 2021
DISCO: accurate Discrete Scale Convolutions Ivan Sosnovik A. Moskalev A. Smeulders 18 31 0 04 Jun 2021
Provably Strict Generalisation Benefit for Invariance in Kernel Methods Bryn Elesedy 8 27 0 04 Jun 2021
Mesh-based graph convolutional neural networks for modeling materials with microstructure A. Frankel C. Safta Coleman Alleman Reese E. Jones 17 15 0 04 Jun 2021
Symmetry-via-Duality: Invariant Neural Network Densities from Parameter-Space Correlators Anindita Maiti Keegan Stoner James Halverson 23 20 0 01 Jun 2021