A Practical Method for Constructing Equivariant Multilayer Perceptrons for Arbitrary Matrix Groups

19 April 2021

Papers citing "A Practical Method for Constructing Equivariant Multilayer Perceptrons for Arbitrary Matrix Groups"

50 / 143 papers shown

Title
Quantifying Robustness: A Benchmarking Framework for Deep Learning Forecasting in Cyber-Physical Systems Alexander Windmann Henrik S. Steude Daniel Boschmann Oliver Niggemann OOD AI4TS 33 0 0 04 Apr 2025
TeleLoRA: Teleporting Model-Specific Alignment Across LLMs Xiao Lin Manoj Acharya Anirban Roy Susmit Jha MoMe 75 0 0 26 Mar 2025
PEnGUiN: Partially Equivariant Graph NeUral Networks for Sample Efficient MARL Joshua McClellan Greyson Brothers Furong Huang Pratap Tokekar 49 0 0 19 Mar 2025
Permutation Equivariant Neural Networks for Symmetric Tensors Edward Pearce-Crump 48 0 0 14 Mar 2025
Equivariant Reinforcement Learning Frameworks for Quadrotor Low-Level Control Beomyeol Yu Taeyoung Lee 39 0 0 27 Feb 2025
Geometric Kolmogorov-Arnold Superposition Theorem Francesco Alesiani Takashi Maruyama H. Christiansen Viktor Zaverkin 57 0 0 23 Feb 2025
Data Augmentation and Regularization for Learning Group Equivariance Oskar Nordenfors Axel Flinth 54 0 0 10 Feb 2025
Revisiting Multi-Permutation Equivariance through the Lens of Irreducible Representations Yonatan Sverdlov Ido Springer Nadav Dym 32 2 0 09 Oct 2024
Learning on LoRAs: GL-Equivariant Processing of Low-Rank Weight Spaces for Large Finetuned Models Theo Putterman Derek Lim Yoav Gelberg Stefanie Jegelka Haggai Maron AI4CE 43 5 0 05 Oct 2024
Symmetry From Scratch: Group Equivariance as a Supervised Learning Task Haozhe Huang Leo Kaixuan Cheng Kaiwen Chen Alán Aspuru-Guzik 30 0 0 05 Oct 2024
Boosting Sample Efficiency and Generalization in Multi-agent Reinforcement Learning via Equivariance Joshua McClellan Naveed Haghani John Winder Furong Huang Pratap Tokekar 27 4 0 03 Oct 2024
Segment as You Wish -- Free-Form Language-Based Segmentation for Medical Images Longchao Da Rui Wang Xiaojian Xu Parminder Bhatia Taha A. Kass-Hout Hua Wei Cao Xiao VLM MedIm 38 2 0 02 Oct 2024
Ensembles provably learn equivariance through data augmentation Oskar Nordenfors Axel Flinth MLT 31 3 0 02 Oct 2024
Symmetry-Based Structured Matrices for Efficient Approximately Equivariant Networks Ashwin Samudre Mircea Petrache Brian D. Nord Shubhendu Trivedi 44 2 0 18 Sep 2024
EqNIO: Subequivariant Neural Inertial Odometry Royina Karegoudra Jayanth Yinshuang Xu Ziyun Wang Evangelos Chatzipantazis Daniel Gehrig Kostas Daniilidis 40 3 0 12 Aug 2024
Beyond Euclid: An Illustrated Guide to Modern Machine Learning with Geometric, Topological, and Algebraic Structures Sophia Sanborn Johan Mathe Mathilde Papillon Domas Buracas Hansen Lillemark Christian Shewmake Abby Bertics Xavier Pennec Nina Miolane 58 4 0 12 Jul 2024
Learning equivariant tensor functions with applications to sparse vector recovery Wilson Gregory Josué Tonelli-Cueto Nicholas F. Marshall Andrew S. Lee Soledad Villar 37 1 0 03 Jun 2024
The Empirical Impact of Neural Parameter Symmetries, or Lack Thereof Derek Lim Moe Putterman Robin Walters Haggai Maron Stefanie Jegelka 35 5 0 30 May 2024
Symmetries in Overparametrized Neural Networks: A Mean-Field View Javier Maass Martínez Joaquin Fontbona FedML MLT 38 2 0 30 May 2024
Neural Isometries: Taming Transformations for Equivariant ML Thomas W. Mitchel Michael Taylor Vincent Sitzmann 28 0 0 29 May 2024
Approximately-symmetric neural networks for quantum spin liquids Dominik S. Kufel Jack Kemp Simon M. Linsel C. Laumann Norman Y. Yao 31 3 0 27 May 2024
Symmetry-Informed Governing Equation Discovery Jianke Yang Wang Rao Nima Dehmamy Robin G. Walters Rose Yu 34 0 0 27 May 2024
Lorentz-Equivariant Geometric Algebra Transformers for High-Energy Physics Jonas Spinner Victor Bresó P. D. Haan Tilman Plehn Jesse Thaler Johann Brehmer AI4CE 29 16 0 23 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
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
RiEMann: Near Real-Time SE(3)-Equivariant Robot Manipulation without Point Cloud Segmentation Chongkai Gao Zhengrong Xue Shuying Deng Tianhai Liang Siqi Yang Lin Shao Huazhe Xu 3DPC 34 10 0 28 Mar 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
Clifford-Steerable Convolutional Neural Networks Maksim Zhdanov David Ruhe Maurice Weiler Ana Lucic Johannes Brandstetter Patrick Forré 47 12 0 22 Feb 2024
Universal Neural Functionals Allan Zhou Chelsea Finn James Harrison 27 12 0 07 Feb 2024
Infinite dSprites for Disentangled Continual Learning: Separating Memory Edits from Generalization Sebastian Dziadzio cCaugatay Yildiz Gido M. van de Ven Tomasz Trzciñski Tinne Tuytelaars Matthias Bethge 19 1 0 27 Dec 2023
Self-Supervised Detection of Perfect and Partial Input-Dependent Symmetries Alonso Urbano David W. Romero 24 1 0 19 Dec 2023
Classification of complex local environments in systems of particle shapes through shape-symmetry encoded data augmentation Shih-Kuang Lee Lee Sun-Ting Tsai S. Glotzer 14 1 0 19 Dec 2023
Symmetry Breaking and Equivariant Neural Networks Sekouba Kaba Siamak Ravanbakhsh 38 12 0 14 Dec 2023
Perspectives on the State and Future of Deep Learning - 2023 Micah Goldblum A. Anandkumar Richard Baraniuk Tom Goldstein Kyunghyun Cho Zachary Chase Lipton Melanie Mitchell Preetum Nakkiran Max Welling Andrew Gordon Wilson 53 4 0 07 Dec 2023
Graph Metanetworks for Processing Diverse Neural Architectures Derek Lim Haggai Maron Marc T. Law Jonathan Lorraine James Lucas AI4CE 31 30 0 07 Dec 2023
Expressive Sign Equivariant Networks for Spectral Geometric Learning Derek Lim Joshua Robinson Stefanie Jegelka Haggai Maron 71 16 0 04 Dec 2023
Steerers: A framework for rotation equivariant keypoint descriptors Georg Bökman Johan Edstedt Michael Felsberg Fredrik Kahl LLMSV 31 10 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
Exactly conservative physics-informed neural networks and deep operator networks for dynamical systems E. Cardoso-Bihlo Alex Bihlo AI4CE PINN 42 4 0 23 Nov 2023
Learning Symmetrization for Equivariance with Orbit Distance Minimization Tien Dat Nguyen Jinwoo Kim Hongseok Yang Seunghoon Hong 30 3 0 13 Nov 2023
Euclidean, Projective, Conformal: Choosing a Geometric Algebra for Equivariant Transformers P. D. Haan Taco S. Cohen Johann Brehmer 28 9 0 08 Nov 2023
Almost Equivariance via Lie Algebra Convolutions Daniel McNeela 26 6 0 19 Oct 2023
Lie Group Decompositions for Equivariant Neural Networks Mircea Mironenco Patrick Forré AI4CE 23 7 0 17 Oct 2023
Efficient Model-Agnostic Multi-Group Equivariant Networks Razan Baltaji Sourya Basu L. Varshney 32 1 0 14 Oct 2023
Learning Layer-wise Equivariances Automatically using Gradients Tycho F. A. van der Ouderaa Alexander Immer Mark van der Wilk MLT 47 12 0 09 Oct 2023
Lie Neurons: Adjoint-Equivariant Neural Networks for Semisimple Lie Algebras Tzu-Yuan Lin Minghan Zhu Maani Ghaffari 40 1 0 06 Oct 2023
Latent Space Symmetry Discovery Jianke Yang Nima Dehmamy Robin G. Walters Rose Yu 30 12 0 29 Sep 2023
Using Multiple Vector Channels Improves E(n)-Equivariant Graph Neural Networks Daniel Levy Sekouba Kaba Carmelo Gonzales Santiago Miret Siamak Ravanbakhsh 38 5 0 06 Sep 2023
CoLA: Exploiting Compositional Structure for Automatic and Efficient Numerical Linear Algebra Andres Potapczynski Marc Finzi Geoff Pleiss Andrew Gordon Wilson 20 7 0 06 Sep 2023
Graph Automorphism Group Equivariant Neural Networks Edward Pearce-Crump William J. Knottenbelt 21 1 0 15 Jul 2023