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Dropout as a Structured Shrinkage Prior, , and . page 4712-4722. (2019)Unifying the Dropout Family Through Structured Shrinkage Priors., and . CoRR, (2018)Learning Priors for Invariance., and . AISTATS, volume 84 of Proceedings of Machine Learning Research, page 366-375. PMLR, (2018)Variational Reference Priors., and . ICLR (Workshop), OpenReview.net, (2017)Predictive Complexity Priors., , and . AISTATS, volume 130 of Proceedings of Machine Learning Research, page 694-702. PMLR, (2021)Do Bayesian Neural Networks Need To Be Fully Stochastic?, , , and . AISTATS, volume 206 of Proceedings of Machine Learning Research, page 7694-7722. PMLR, (2023)Calibrated Learning to Defer with One-vs-All Classifiers., and . ICML, volume 162 of Proceedings of Machine Learning Research, page 22184-22202. PMLR, (2022)Hybrid Models with Deep and Invertible Features., , , , and . ICML, volume 97 of Proceedings of Machine Learning Research, page 4723-4732. PMLR, (2019)Anytime-Valid Confidence Sequences for Consistent Uncertainty Estimation in Early-Exit Neural Networks., , , , and . CoRR, (2023)Normalizing Flows for Probabilistic Modeling and Inference., , , , and . J. Mach. Learn. Res., (2021)