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- W2992005611 abstract "Normalizing Flows are generative models which produce tractable distributions where both sampling and density evaluation can be efficient and exact. The goal of this survey article is to give a coherent and comprehensive review of the literature around the construction and use of Normalizing Flows for distribution learning. We aim to provide context and explanation of the models, review current state-of-the-art literature, and identify open questions and promising future directions." @default.
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- W2992005611 date "2021-11-01" @default.
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- W2992005611 title "Normalizing Flows: An Introduction and Review of Current Methods" @default.
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- W2992005611 doi "https://doi.org/10.1109/tpami.2020.2992934" @default.
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