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This paper presents a methodology and numerical algorithms for constructing accelerated gradient flows on the space of probability distributions.
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Xiang Cheng, Niladri S Chatterji, Peter L Bartlett, and Michael I Jordan · 2017
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Prateek Jain, Sham M Kakade, Rahul Kidambi, Praneeth Netrapalli, and Aaron Sidford · 2017
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Pierre H Richemond and Brendan Maginnis · 2017
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Michael Betancourt, Michael I Jordan, and Ashia C Wilson · 2018
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A unified particle-optimization framework for scalable bayesian sampling
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Martin Arjovsky, Soumith Chintala, and Léon Bottou · 2017
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David M Blei, Alp Kucukelbir, and Jon D McAuliffe · 2017
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On the global convergence of gradient descent for over-parameterized models using optimal transport
Lenaic Chizat and Francis Bach · 2018
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Approximate inference with wasserstein gradient flows
Charlie Frogner and Tomaso Poggio · 2018
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Policy optimization as wasserstein gradient flows
Ruiyi Zhang, Changyou Chen, Chunyuan Li, and Lawrence Carin · 2018
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