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Scalable Variational Inference in Log-supermodular Models.

, и . ICML, том 37 из JMLR Workshop and Conference Proceedings, стр. 1804-1813. JMLR.org, (2015)

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Scalable Variational Inference in Log-supermodular Models., и . ICML, том 37 из JMLR Workshop and Conference Proceedings, стр. 1804-1813. JMLR.org, (2015)The Visual Task Adaptation Benchmark, , , , , , , , , и 7 other автор(ы). (2019)cite arxiv:1910.04867.Improving Optimization-Based Approximate Inference by Clamping Variables., , , и . UAI, AUAI Press, (2017)Variational Inference in Mixed Probabilistic Submodular Models., , и . NIPS, стр. 1759-1767. (2016)On Mutual Information Maximization for Representation Learning., , , , и . ICLR, OpenReview.net, (2020)Revisiting the Calibration of Modern Neural Networks., , , , , , , и . NeurIPS, стр. 15682-15694. (2021)Evaluating Generative Models Using Divergence Frontiers., , , , , и . CoRR, (2019)Scaling Vision Transformers to 22 Billion Parameters., , , , , , , , , и 32 other автор(ы). CoRR, (2023)Uncertainty Baselines: Benchmarks for Uncertainty & Robustness in Deep Learning., , , , , , , , , и 14 other автор(ы). CoRR, (2021)You Only Train Once: Loss-Conditional Training of Deep Networks., и . ICLR, OpenReview.net, (2020)