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How Good is the Bayes Posterior in Deep Neural Networks Really?, , , , , , , , , and . (2020)cite arxiv:2002.02405.Proximal Methods for Hierarchical Sparse Coding., , , and . J. Mach. Learn. Res., (2011)Pi-DUAL: Using Privileged Information to Distinguish Clean from Noisy Labels., , , , , and . CoRR, (2023)Scaling Vision with Sparse Mixture of Experts., , , , , , , and . NeurIPS, page 8583-8595. (2021)The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks., , , , , , , , , and . ICML, volume 119 of Proceedings of Machine Learning Research, page 9289-9299. PMLR, (2020)Scaling Vision Transformers to 22 Billion Parameters., , , , , , , , , and 32 other author(s). CoRR, (2023)Uncertainty Baselines: Benchmarks for Uncertainty & Robustness in Deep Learning., , , , , , , , , and 14 other author(s). CoRR, (2021)Structured Sparsity through Convex Optimization, , , and . Statistical Science, 27 (4): 450--468 (November 2012)Multimodal Contrastive Learning with LIMoE: the Language-Image Mixture of Experts., , , , and . NeurIPS, (2022)Hyperparameter Ensembles for Robustness and Uncertainty Quantification., , , and . NeurIPS, (2020)