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Normalizing Flows for Probabilistic Modeling and Inference

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Dec 06 2019 Danilo J. Rezende

Looking for something to read in your flight to #NeurIPS2019? Read about Normalizing Flows from our extensive review paper (also with new insights on how to think about and derive new flows) https://arxiv.org/abs/1912.02762 with @gpapamak @eric_nalisnick @DeepSpiker @balajiln @shakir_za https://t.co/EWh8Aui7n0
11 replies, 648 likes


Dec 06 2019 George Papamakarios

Check out our extensive review paper on normalizing flows! This paper is the product of years of thinking about flows: it contains everything we know about them, and many new insights. With @eric_nalisnick, @DeepSpiker, @shakir_za, @balajiln. http://arxiv.org/abs/1912.02762 Thread 👇
4 replies, 629 likes


Dec 07 2019 Andrej Karpathy

This is very well done and readable, thank you so much for putting it together! (was starting to be hard to keep track of the individual papers and how they relate) Normalizing Flows are very powerful and should become a part of any deep learning researcher/practitioner's toolbox
5 replies, 479 likes


Jan 17 2020 David Duvenaud

This review on normalizing flows is excellent. It's full of clear writing, precise claims, and useful connections.
0 replies, 140 likes


Dec 06 2019 Eric Nalisnick

Indeed, what better way to spend your flight than immersed in 60 pages of all things flow. Happy to hear any feedback (oversights, clarity issues, etc).
3 replies, 64 likes


Dec 06 2019 Statistics Papers

Normalizing Flows for Probabilistic Modeling and Inference. http://arxiv.org/abs/1912.02762
0 replies, 53 likes


Dec 06 2019 jörn jacobsen

Fantastic summary of the state of the art and open problems in normalizing flows!
0 replies, 30 likes


Dec 08 2019 no love deep learning ✈ NeuHYPE19

we'll have open-mic sessions to ignite discussions, as well as invited spotlights! First one will be @eric_nalisnick (@CambridgeMLG & @DeepMindAI ) talking about prospects and challenges of #tractable Inference with #Flows check his survey with @gpapamak https://arxiv.org/abs/1912.02762
1 replies, 9 likes


Feb 01 2020 no love deep learning

@martin_trapp Even without using mixtures one might easily fit those 2D densities with more expressive single models...eg #flows and #autoeegressive ones They *are* also tractable for complete evidence, but not marginals Cf. cool survey by @eric_nalisnick @gpapamak http://arxiv.org/abs/1912.02762
1 replies, 8 likes


Dec 06 2019 Adam Kosiorek

The most comprehensive overview of normalizing flows to date!
0 replies, 8 likes


Jan 19 2020 Roman Shapovalov

This tutorial is gold. Very accessible, comprehensive, and up-to-date. Thanks @gpapamak et al.!
0 replies, 5 likes


Dec 07 2019 Bo Wang

This is very useful resource for anyone who is interested in deep learning research!
0 replies, 5 likes


Dec 06 2019 Dennis Prangle

One for the ever-lengthening must-read list
1 replies, 4 likes


Dec 06 2019 Hyunjik Kim

Review paper on flows from the experts!
0 replies, 4 likes


Dec 08 2019 KUNDAN KUMAR

Read it. Amazing!!
0 replies, 1 likes


Jan 09 2020 Gabriel Bernier-Colborne

Great survey paper on normalizing flows: https://arxiv.org/abs/1912.02762
0 replies, 1 likes


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