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Last Layer Re-Training is Sufficient for Robustness to Spurious Correlations.

, , and . ICLR, OpenReview.net, (2023)

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Loss Surfaces, Mode Connectivity, and Fast Ensembling of DNNs., , , , and . NeurIPS, page 8803-8812. (2018)On Feature Learning in the Presence of Spurious Correlations., , , and . NeurIPS, (2022)A Simple Baseline for Bayesian Uncertainty in Deep Learning., , , , and . NeurIPS, page 13132-13143. (2019)Semi-Supervised Learning with Normalizing Flows., , , and . ICML, volume 119 of Proceedings of Machine Learning Research, page 4615-4630. PMLR, (2020)Generalizing Convolutional Neural Networks for Equivariance to Lie Groups on Arbitrary Continuous Data., , , and . ICML, volume 119 of Proceedings of Machine Learning Research, page 3165-3176. PMLR, (2020)Last Layer Re-Training is Sufficient for Robustness to Spurious Correlations., , and . ICLR, OpenReview.net, (2023)FlexiViT: One Model for All Patch Sizes., , , , , , , , , and . CVPR, page 14496-14506. IEEE, (2023)Dangers of Bayesian Model Averaging under Covariate Shift., , , and . NeurIPS, page 3309-3322. (2021)On Uncertainty, Tempering, and Data Augmentation in Bayesian Classification., , , and . NeurIPS, (2022)There Are Many Consistent Explanations of Unlabeled Data: Why You Should Average., , , and . ICLR (Poster), OpenReview.net, (2019)