representation theory

Data Augmentation: A Fourier Analysis Perspective COLT 2026 On the Statistical Query Complexity of Learning Semiautomata: a Random Walk Approach COLT 2026 A Characterization Theorem for Equivariant Networks with Point-wise Activations ICLR 2024 Steerers: A Framework for Rotation Equivariant Keypoint Descriptors CVPR 2024 Actionable Neural Representations: Grid Cells from Minimal Constraints ICLR 2023 A Toy Model of Universality: Reverse Engineering how Networks Learn Group Operations ICML 2023 A Classification of G-invariant Shallow Neural Networks NeurIPS 2022 PDO-s3DCNNs: Partial Differential Operator Based Steerable 3D CNNs ICML 2022 Real-Valued Backpropagation is Unsuitable for Complex-Valued Neural Networks NeurIPS 2022 Understanding Hyperdimensional Computing for Parallel Single-Pass Learning NeurIPS 2022 Universality of Group Convolutional Neural Networks Based on Ridgelet Analysis on Groups NeurIPS 2022 Analytic Characterization of the Hessian in Shallow ReLU Models: A Tale of Symmetry NeurIPS 2020 Sharp Representation Theorems for ReLU Networks with Precise Dependence on Depth NeurIPS 2020 Unsupervised Co-Learning on G-Manifolds Across Irreducible Representations NeurIPS 2019 On the Generalization of Equivariance and Convolution in Neural Networks to the Action of Compact Groups ICML 2018 A Representation Theory for Ranking Functions NeurIPS 2014