{"total":22,"rows":[{"id":"2105.13926","title":"Geometric Deep Learning and Equivariant Neural Networks","created":"2021-05-28","cited_by_count":65,"area":null},{"id":"2202.07230","title":"Geometrically Equivariant Graph Neural Networks: A Survey","created":"2022-02-15","cited_by_count":56,"area":null},{"id":"2305.11141","title":"Clifford Group Equivariant Neural Networks","created":"2023-05-18","cited_by_count":55,"area":null},{"id":"2202.03990","title":"Equivariance versus Augmentation for Spherical Images","created":"2022-02-08","cited_by_count":24,"area":null},{"id":"2209.13603","title":"Scalable and Equivariant Spherical CNNs by Discrete-Continuous (DISCO) Convolutions","created":"2022-09-27","cited_by_count":24,"area":null},{"id":"2105.05400","title":"Homogeneous vector bundles and $G$-equivariant convolutional neural networks","created":"2021-05-12","cited_by_count":21,"area":null},{"id":"2211.02504","title":"Geometry-Complete Perceptron Networks for 3D Molecular Graphs","created":"2022-11-04","cited_by_count":16,"area":null},{"id":"2305.18983","title":"SO(2)-Equivariant Downwash Models for Close Proximity Flight","created":"2023-05-30","cited_by_count":7,"area":null},{"id":"2309.02898","title":"A Unified Framework for Discovering Discrete Symmetries","created":"2023-09-06","cited_by_count":7,"area":null},{"id":"2311.18672","title":"A Comparison Between Invariant and Equivariant Classical and Quantum Graph Neural Networks","created":"2023-11-30","cited_by_count":6,"area":null},{"id":"2302.11349","title":"Steerable Equivariant Representation Learning","created":"2023-02-22","cited_by_count":5,"area":null},{"id":"2211.07482","title":"Unifying O(3) Equivariant Neural Networks Design with Tensor-Network Formalism","created":"2022-11-14","cited_by_count":3,"area":null},{"id":"2408.00949","title":"Equivariant neural networks and piecewise linear representation theory","created":"2024-08-01","cited_by_count":3,"area":null},{"id":"2303.01567","title":"Deep Neural Networks with Efficient Guaranteed Invariances","created":"2023-03-02","cited_by_count":2,"area":null},{"id":"2309.05352","title":"Neural Discovery of Permutation Subgroups","created":"2023-09-11","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":"2210.16646","title":"Breaking the Symmetry: Resolving Symmetry Ambiguities in Equivariant Neural Networks","created":"2022-10-29","cited_by_count":1,"area":null},{"id":"2211.15903","title":"Equivalence Between SE(3) Equivariant Networks via Steerable Kernels and Group Convolution","created":"2022-11-29","cited_by_count":1,"area":null},{"id":"2510.21691","title":"On Uncertainty Calibration for Equivariant Functions","created":"2025-10-24","cited_by_count":1,"area":null},{"id":"2412.09927","title":"Neural Vector Tomography for Reconstructing a Magnetization Vector Field","created":"2024-12-13","cited_by_count":0,"area":null},{"id":"2602.05352","title":"Smoothness Errors in Dynamics Models and How to Avoid Them","created":"2026-02-05","cited_by_count":0,"area":null},{"id":"2609.04583","title":"Representation Redundancy and Structural Complexity in Finite-Field Inversion","created":"2026-09-04","cited_by_count":0,"area":null}],"next_cursor":null}