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Combining Ensembles and Data Augmentation Can Harm Your Calibration.

, , , , , , и . ICLR, OpenReview.net, (2021)

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Michael Snoek

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Learning Latent Permutations with Gumbel-Sinkhorn Networks., , , и . ICLR (Poster), OpenReview.net, (2018)On Nonparametric Guidance for Learning Autoencoder Representations., , и . AISTATS, том 22 из JMLR Proceedings, стр. 1073-1080. JMLR.org, (2012)Deep Learning for Bayesian Optimization of Scientific Problems with High-Dimensional Structure., , , , , и . Trans. Mach. Learn. Res., (2022)Sparse MoEs meet Efficient Ensembles., , , , , , , , , и 3 other автор(ы). Trans. Mach. Learn. Res., (2022)Nonparametric guidance of autoencoder representations using label information., , и . J. Mach. Learn. Res., (2012)Revisiting One-vs-All Classifiers for Predictive Uncertainty and Out-of-Distribution Detection in Neural Networks., , , , , и . CoRR, (2020)Combining Ensembles and Data Augmentation can Harm your Calibration., , , , , , и . CoRR, (2020)Predicting the utility of search spaces for black-box optimization: a simple, budget-aware approach., , , , , и . CoRR, (2021)Uncertainty Baselines: Benchmarks for Uncertainty & Robustness in Deep Learning., , , , , , , , , и 14 other автор(ы). CoRR, (2021)From Videos to Places: Geolocating the World's Videos., , и . ICDM Workshops, стр. 823-832. IEEE Computer Society, (2011)