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Challenges and Perspectives in Deep Generative Modeling (Dagstuhl Seminar 23072)., , , , и . Dagstuhl Reports, 13 (2): 47-70 (февраля 2023)PACOH: Bayes-Optimal Meta-Learning with PAC-Guarantees., , , и . ICML, том 139 из Proceedings of Machine Learning Research, стр. 9116-9126. PMLR, (2021)Repulsive Deep Ensembles are Bayesian., и . NeurIPS, стр. 3451-3465. (2021)Priors in Bayesian Deep Learning: A Review.. CoRR, (2021)Neural Variational Gradient Descent., , и . CoRR, (2021)On the Choice of Priors in Bayesian Deep Learning.. ETH Zurich, Zürich, Switzerland, (2021)base-search.net (ftethz:oai:www.research-collection.ethz.ch:20.500.11850/523269).Conservative Uncertainty Estimation By Fitting Prior Networks., , , , и . ICLR, OpenReview.net, (2020)Invariance Learning in Deep Neural Networks with Differentiable Laplace Approximations., , , , и . NeurIPS, (2022)Towards Dynamic Feature Acquisition on Medical Time Series by Maximizing Conditional Mutual Information., , , и . CoRR, (2024)On the Challenges and Opportunities in Generative AI., , , , , , , , , и 15 other автор(ы). CoRR, (2024)