invariance learning

Improving Prompt Generalization for Cross-prompt Essay Trait Scoring from the Scoring-invariance Perspective EMNLP 2025 Continuous Invariance Learning ICLR 2024 The Implicit Bias of Heterogeneity towards Invariance: A Study of Multi-Environment Matrix Sensing NeurIPS 2024 How Much Data Are Augmentations Worth? An Investigation into Scaling Laws, Invariance, and Implicit Regularization ICLR 2023 Learning to Transform for Generalizable Instance-wise Invariance ICCV 2023 Deep invariant networks with differentiable augmentation layers NeurIPS 2022 Do deep networks transfer invariances across classes? ICLR 2022 Invariance Learning based on Label Hierarchy NeurIPS 2022 Invariance Learning in Deep Neural Networks with Differentiable Laplace Approximations NeurIPS 2022 Last Layer Marginal Likelihood for Invariance Learning AISTATS 2022 VICRegL: Self-Supervised Learning of Local Visual Features NeurIPS 2022 Grounding inductive biases in natural images: invariance stems from variations in data NeurIPS 2021 Learning with invariances in random features and kernel models COLT 2021 Learning Invariances in Neural Networks from Training Data NeurIPS 2020 Efficient Augmentation via Data Subsampling ICLR 2019 Non-Parametric Transformation Networks for Learning General Invariances from Data AAAI 2019 Learning Invariances using the Marginal Likelihood NeurIPS 2018 Learning to Exploit Invariances in Clinical Time-Series Data using Sequence Transformer Networks MLHC 2018 iLab-20M: A Large-Scale Controlled Object Dataset to Investigate Deep Learning CVPR 2016 Direct Modeling of Complex Invariances for Visual Object Features ICML 2013 Learning with Invariance via Linear Functionals on Reproducing Kernel Hilbert Space NeurIPS 2013 On Nonparametric Guidance for Learning Autoencoder Representations AISTATS 2012 Learning invariant features using the Transformed Indian Buffet Process NeurIPS 2010 Convex Learning with Invariances NeurIPS 2007