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
Group Downsampling with Equivariant Anti-aliasing Md Ashiqur Rahman Raymond A. Yeh 65 1 0 24 Apr 2025
Permutation Equivariant Neural Networks for Symmetric Tensors Edward Pearce-Crump 48 0 0 14 Mar 2025
SO(3)-Equivariant Neural Networks for Learning Vector Fields on Spheres Francesco Ballerin Nello Blaser E. Grong 62 0 0 13 Mar 2025
Shifting the Paradigm: A Diffeomorphism Between Time Series Data Manifolds for Achieving Shift-Invariancy in Deep Learning B. U. Demirel Christian Holz OOD AI4TS 72 0 0 27 Feb 2025
Enhancing the Scalability and Applicability of Kohn-Sham Hamiltonians for Molecular Systems Yunyang Li Zaishuo Xia Lin Huang Xinran Wei Han Yang ... Zun Wang Chang-Shu Liu Jia Zhang Bin Shao Mark B. Gerstein 72 0 0 26 Feb 2025
MatrixNet: Learning over symmetry groups using learned group representations Lucas Laird Circe Hsu Asilata Bapat Robin Walters AI4CE 43 0 0 17 Jan 2025
Equivariant Action Sampling for Reinforcement Learning and Planning Linfeng Zhao Owen Howell Xupeng Zhu Jung Yeon Park Zhewen Zhang Robin Walters Lawson L. S. Wong 94 2 0 16 Dec 2024
AsCAN: Asymmetric Convolution-Attention Networks for Efficient Recognition and Generation Anil Kag Huseyin Coskun Jierun Chen Junli Cao Willi Menapace Aliaksandr Siarohin Sergey Tulyakov Jian Ren 46 3 0 07 Nov 2024
Optimal Equivariant Architectures from the Symmetries of Matrix-Element Likelihoods Daniel Maître Vishal S. Ngairangbam M. Spannowsky 29 4 0 24 Oct 2024
On the VC dimension of deep group convolutional neural networks Anna Sepliarskaia S. Langer Johannes Schmidt-Hieber MLT 28 0 0 21 Oct 2024
Revisiting Multi-Permutation Equivariance through the Lens of Irreducible Representations Yonatan Sverdlov Ido Springer Nadav Dym 32 2 0 09 Oct 2024
Unitary convolutions for learning on graphs and groups B. Kiani Lukas Fesser Melanie Weber GNN 37 1 0 07 Oct 2024
Ensembles provably learn equivariance through data augmentation Oskar Nordenfors Axel Flinth MLT 31 3 0 02 Oct 2024
On the universality of neural encodings in CNNs Florentin Guth Brice Ménard SSL 48 5 0 28 Sep 2024
Symmetry-Based Structured Matrices for Efficient Approximately Equivariant Networks Ashwin Samudre Mircea Petrache Brian D. Nord Shubhendu Trivedi 42 2 0 18 Sep 2024
Improving Equivariant Model Training via Constraint Relaxation Stefanos Pertigkiozoglou Evangelos Chatzipantazis Shubhendu Trivedi Kostas Daniilidis 37 4 0 23 Aug 2024
Relaxed Rotational Equivariance via $G$ -Biases in Vision Zhiqiang Wu Licheng Sun Yingjie Liu Jian Yang Hanlin Dong S. J. Lin Xuan Tang Jinpeng Mi Bo Jin Xian Wei 31 0 0 22 Aug 2024
Optimal Symmetries in Binary Classification Vishal S. Ngairangbam M. Spannowsky 34 1 0 16 Aug 2024
Stability Analysis of Equivariant Convolutional Representations Through The Lens of Equivariant Multi-layered CKNs Soutrik Roy Chowdhury 38 0 0 08 Aug 2024
The Selective G-Bispectrum and its Inversion: Applications to G-Invariant Networks Simon Mataigne Johan Mathe Sophia Sanborn Christopher Hillar Nina Miolane 28 0 0 10 Jul 2024
Understanding the Role of Invariance in Transfer Learning Till Speicher Vedant Nanda Krishna P. Gummadi SSL OOD 40 1 0 05 Jul 2024
Learning Color Equivariant Representations Felix O'Mahony Yulong Yang Christine Allen-Blanchette 28 0 0 13 Jun 2024
Equivariance via Minimal Frame Averaging for More Symmetries and Efficiency Yuchao Lin Jacob Helwig Shurui Gui Shuiwang Ji 39 7 0 11 Jun 2024
Equivariant Neural Tangent Kernels Philipp Misof Pan Kessel Jan E. Gerken 50 0 0 10 Jun 2024
FlowMM: Generating Materials with Riemannian Flow Matching Benjamin Kurt Miller Ricky T. Q. Chen Anuroop Sriram Brandon M. Wood 29 32 0 07 Jun 2024
Symmetries in Overparametrized Neural Networks: A Mean-Field View Javier Maass Martínez Joaquin Fontbona FedML MLT 33 2 0 30 May 2024
Transport of Algebraic Structure to Latent Embeddings Samuel Pfrommer Brendon G. Anderson Somayeh Sojoudi 29 0 0 27 May 2024
Enhancing lattice kinetic schemes for fluid dynamics with Lattice-Equivariant Neural Networks Giulio Ortali Alessandro Gabbana Imre Atmodimedjo Alessandro Corbetta AI4CE 68 1 0 22 May 2024
Spectral Convolutional Conditional Neural Processes Peiman Mohseni Nick Duffield 27 3 0 19 Apr 2024
Symmetry: a General Structure in Nonparametric Regression Louis Christie John A. D. Aston 34 0 0 19 Apr 2024
How Deep Networks Learn Sparse and Hierarchical Data: the Sparse Random Hierarchy Model Umberto M. Tomasini M. Wyart BDL 35 7 0 16 Apr 2024
Equivariant graph convolutional neural networks for the representation of homogenized anisotropic microstructural mechanical response Ravi G. Patel C. Safta Reese E. Jones AI4CE 35 1 0 05 Apr 2024
Pooling Image Datasets With Multiple Covariate Shift and Imbalance Sotirios Panagiotis Chytas Vishnu Suresh Lokhande Peiran Li Vikas Singh OOD 30 0 0 05 Mar 2024
Structure Preserving Diffusion Models Haoye Lu S. Szabados Yaoliang Yu DiffM 59 2 0 29 Feb 2024
A unified Fourier slice method to derive ridgelet transform for a variety of depth-2 neural networks Sho Sonoda Isao Ishikawa Masahiro Ikeda 41 4 0 25 Feb 2024
G-RepsNet: A Fast and General Construction of Equivariant Networks for Arbitrary Matrix Groups Sourya Basu Suhas Lohit Matthew Brand 34 0 0 23 Feb 2024
Geometry-Informed Neural Networks Arturs Berzins Andreas Radler Sebastian Sanokowski Sepp Hochreiter Johannes Brandstetter GAN AI4CE 35 1 0 21 Feb 2024
Global optimality under amenable symmetry constraints Peter Orbanz 15 0 0 12 Feb 2024
Universal Neural Functionals Allan Zhou Chelsea Finn James Harrison 27 12 0 07 Feb 2024
Equivariant Symmetry Breaking Sets YuQing Xie Tess E. Smidt 22 4 0 05 Feb 2024
Equivariant Manifold Neural ODEs and Differential Invariants Emma Andersdotter Fredrik Ohlsson 26 0 0 25 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
Scalable Normalizing Flows Enable Boltzmann Generators for Macromolecules Joseph C. Kim David Bloore Karan Kapoor Jun Feng Ming-Hong Hao Mengdi Wang 37 7 0 08 Jan 2024
Rotation Equivariant Proximal Operator for Deep Unfolding Methods in Image Restoration J. Fu Qi Xie Deyu Meng Zongben Xu 11 4 0 25 Dec 2023
Harmonics of Learning: Universal Fourier Features Emerge in Invariant Networks G. Marchetti Christopher Hillar Danica Kragic Sophia Sanborn 17 12 0 13 Dec 2023
Topological Obstructions and How to Avoid Them Babak Esmaeili Robin G. Walters Heiko Zimmermann Jan Willem van de Meent AI4CE 24 3 0 12 Dec 2023
Grokking Group Multiplication with Cosets Dashiell Stander Qinan Yu Honglu Fan Stella Biderman 33 9 0 11 Dec 2023
Learning to be Simple Yang-Hui He Vishnu Jejjala Challenger Mishra Max Sharnoff 17 0 0 08 Dec 2023
Expressive Sign Equivariant Networks for Spectral Geometric Learning Derek Lim Joshua Robinson Stefanie Jegelka Haggai Maron 71 16 0 04 Dec 2023
Affine Invariance in Continuous-Domain Convolutional Neural Networks A. Mohaddes Johannes Lederer 13 1 0 13 Nov 2023