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VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning., , , , , , и . ICLR, OpenReview.net, (2020)Uncertainty Quantification with Statistical Guarantees in End-to-End Autonomous Driving Control., , , , , и . ICRA, стр. 7344-7350. IEEE, (2020)Radial Bayesian Neural Networks: Beyond Discrete Support In Large-Scale Bayesian Deep Learning, , и . (2019)cite arxiv:1907.00865.Active Learning under Pool Set Distribution Shift and Noisy Data., , и . CoRR, (2021)Shifts: A Dataset of Real Distributional Shift Across Multiple Large-Scale Tasks., , , , , , , , , и 5 other автор(ы). CoRR, (2021)Quantifying Uncertainty for Machine Learning Based Diagnostic., , , и . CoRR, (2021)Prioritized training on points that are learnable, worth learning, and not yet learned., , , , , , , , , и . CoRR, (2021)Dropout as a Bayesian Approximation: Appendix, и . (2015)cite arxiv:1506.02157Comment: 20 pages, 1 figure; ICML proceedings version.PsiPhi-Learning: Reinforcement Learning with Demonstrations using Successor Features and Inverse Temporal Difference Learning., , , , , и . ICML, том 139 из Proceedings of Machine Learning Research, стр. 3305-3317. PMLR, (2021)Identifying Causal-Effect Inference Failure with Uncertainty-Aware Models., , , и . NeurIPS, (2020)