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Uncertainty Estimation via Stochastic Batch Normalization.

, , , , and . ISNN (1), volume 11554 of Lecture Notes in Computer Science, page 261-269. Springer, (2019)

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Reintroducing Straight-Through Estimators as Principled Methods for Stochastic Binary Networks., , , and . CoRR, (2020)Uncertainty Estimation via Stochastic Batch Normalization., , , , and . ISNN (1), volume 11554 of Lecture Notes in Computer Science, page 261-269. Springer, (2019)Variance Networks: When Expectation Does Not Meet Your Expectations, , , and . International Conference on Learning Representations, (2019)Greedy Policy Search: A Simple Baseline for Learnable Test-Time Augmentation., , , , and . UAI, volume 124 of Proceedings of Machine Learning Research, page 1308-1317. AUAI Press, (2020)Bayesian Incremental Learning for Deep Neural Networks., , , , , and . ICLR (Workshop), OpenReview.net, (2018)Variational Dropout via Empirical Bayes., , and . CoRR, (2018)Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning., , , and . CoRR, (2020)Structured Bayesian Pruning via Log-Normal Multiplicative Noise., , , and . NIPS, page 6775-6784. (2017)Uncertainty Estimation via Stochastic Batch Normalization., , , , and . ICLR (Workshop), OpenReview.net, (2018)Doubly Semi-Implicit Variational Inference., , , and . CoRR, (2018)