group invariance

Data Augmentation: A Fourier Analysis Perspective COLT 2026 Efficient Learning and Symmetry Discovery under Exact Invariances COLT 2026 A Robust Kernel Statistical Test of Invariance: Detecting Subtle Asymmetries AISTATS 2025 Harmonics of Learning: Universal Fourier Features Emerge in Invariant Networks COLT 2024 Sample-efficient Bayesian Optimisation Using Known Invariances NeurIPS 2024 The Selective G-Bispectrum and its Inversion: Applications to G-Invariant Networks NeurIPS 2024 Bispectral Neural Networks ICLR 2023 Densely Connected G-invariant Deep Neural Networks with Signed Permutation Representations JMLR 2023 Neural approximation of Wasserstein distance via a universal architecture for symmetric and factorwise group invariant functions NeurIPS 2023 On the Implicit Bias of Linear Equivariant Steerable Networks NeurIPS 2023 Probabilistic Invariant Learning with Randomized Linear Classifiers NeurIPS 2023 The Exact Sample Complexity Gain from Invariances for Kernel Regression NeurIPS 2023 A Classification of G-invariant Shallow Neural Networks NeurIPS 2022 Unsupervised Learning of Group Invariant and Equivariant Representations NeurIPS 2022 Improved generalization bounds of group invariant / equivariant deep networks via quotient feature spaces UAI 2021 Neural Networks for Learning Counterfactual G-Invariances from Single Environments ICLR 2021 On the Sample Complexity of Learning under Geometric Stability NeurIPS 2021 Systematic generalisation with group invariant predictions ICLR 2021 Probabilistic Symmetries and Invariant Neural Networks JMLR 2020 On the Universality of Invariant Networks ICML 2019 Group Invariance Principles for Causal Generative Models AISTATS 2018 Learning with Group Invariant Features: A Kernel Perspective. NeurIPS 2015