{"total":34,"rows":[{"id":"2110.02905","title":"Geometric and Physical Quantities Improve E(3) Equivariant Message Passing","created":"2021-10-06","cited_by_count":228,"area":null},{"id":"2102.10333","title":"Provably Strict Generalisation Benefit for Equivariant Models","created":"2021-02-20","cited_by_count":91,"area":null},{"id":"2105.13926","title":"Geometric Deep Learning and Equivariant Neural Networks","created":"2021-05-28","cited_by_count":65,"area":null},{"id":"2410.23179","title":"Does equivariance matter at scale?","created":"2024-10-30","cited_by_count":52,"area":null},{"id":"2106.02346","title":"Provably Strict Generalisation Benefit for Invariance in Kernel Methods","created":"2021-06-04","cited_by_count":30,"area":null},{"id":"2110.04495","title":"Multi-Agent MDP Homomorphic Networks","created":"2021-10-09","cited_by_count":25,"area":null},{"id":"2110.13059","title":"Exploiting Redundancy: Separable Group Convolutional Networks on Lie Groups","created":"2021-10-25","cited_by_count":22,"area":null},{"id":"2111.05529","title":"Understanding the Generalization Benefit of Model Invariance from a Data Perspective","created":"2021-11-10","cited_by_count":22,"area":null},{"id":"2201.12176","title":"Generative Coarse-Graining of Molecular Conformations","created":"2022-01-28","cited_by_count":21,"area":null},{"id":"2102.06942","title":"Rotation-Equivariant Deep Learning for Diffusion MRI","created":"2021-02-13","cited_by_count":20,"area":null},{"id":"2504.08896","title":"Position: Beyond Euclidean -- Foundation Models Should Embrace Non-Euclidean Geometries","created":"2025-04-11","cited_by_count":18,"area":null},{"id":"2206.05398","title":"E2PN: Efficient SE(3)-Equivariant Point Network","created":"2022-06-11","cited_by_count":17,"area":null},{"id":"2210.12124","title":"Equivariant Networks for Zero-Shot Coordination","created":"2022-10-21","cited_by_count":16,"area":null},{"id":"2304.02628","title":"What Affects Learned Equivariance in Deep Image Recognition Models?","created":"2023-04-05","cited_by_count":15,"area":null},{"id":"2206.01693","title":"Three-dimensional microstructure generation using generative adversarial neural networks in the context of continuum micromechanics","created":"2022-05-31","cited_by_count":11,"area":null},{"id":"2312.13534","title":"SE(3)-Equivariant and Noise-Invariant 3D Rigid Motion Tracking in Brain MRI","created":"2023-12-21","cited_by_count":10,"area":null},{"id":"2210.00935","title":"Analysis of (sub-)Riemannian PDE-G-CNNs","created":"2022-10-03","cited_by_count":8,"area":null},{"id":"2306.13960","title":"Regular SE(3) Group Convolutions for Volumetric Medical Image Analysis","created":"2023-06-24","cited_by_count":6,"area":null},{"id":"2310.04521","title":"Lie Neurons: Adjoint-Equivariant Neural Networks for Semisimple Lie Algebras","created":"2023-10-06","cited_by_count":6,"area":null},{"id":"2202.12795","title":"Equilibrium Aggregation: Encoding Sets via Optimization","created":"2022-02-25","cited_by_count":5,"area":null},{"id":"2204.10436","title":"Scale-Equivariant Unrolled Neural Networks for Data-Efficient Accelerated MRI Reconstruction","created":"2022-04-21","cited_by_count":5,"area":null},{"id":"2408.00082","title":"TASI Lectures on Physics for Machine Learning","created":"2024-07-31","cited_by_count":5,"area":null},{"id":"2504.10777","title":"AtlasD: Automatic Local Symmetry Discovery","created":"2025-04-15","cited_by_count":5,"area":null},{"id":"2405.02795","title":"Graph as Point Set","created":"2024-05-05","cited_by_count":4,"area":null},{"id":"2403.19612","title":"ILPO-NET: Network for the invariant recognition of arbitrary volumetric patterns in 3D","created":"2024-03-28","cited_by_count":3,"area":null},{"id":"2208.12146","title":"A Feedforward Unitary Equivariant Neural Network","created":"2022-08-25","cited_by_count":2,"area":null},{"id":"2409.07327","title":"Current Symmetry Group Equivariant Convolution Frameworks for Representation Learning","created":"2024-09-11","cited_by_count":2,"area":null},{"id":"2410.12831","title":"Segment as You Wish -- Free-Form Language-Based Segmentation for Medical Images","created":"2024-10-02","cited_by_count":2,"area":null},{"id":"2403.14897","title":"Geometric Generative Models based on Morphological Equivariant PDEs and GANs","created":"2024-03-22","cited_by_count":1,"area":null},{"id":"2404.15979","title":"On the Fourier analysis in the SO(3) space : EquiLoPO Network","created":"2024-04-24","cited_by_count":1,"area":null},{"id":"2103.15551","title":"Toward Building Science Discovery Machines","created":"2021-03-24","cited_by_count":0,"area":null},{"id":"2311.09245","title":"Affine Invariance in Continuous-Domain Convolutional Neural Networks","created":"2023-11-13","cited_by_count":0,"area":null},{"id":"2512.08888","title":"Accelerated Rotation-Invariant Convolution for UAV Image Segmentation","created":"2025-12-09","cited_by_count":0,"area":null},{"id":"2605.15368","title":"Discretizing Group-Convolutional Neural Networks for 3D Geometry in Feature Space","created":"2026-05-14","cited_by_count":0,"area":null}],"next_cursor":null}