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Normalizing flows are a widely used class of latent-variable generative models with a tractable likelihood.
Is there an analog of nesterov acceleration for mcmc?
Yi-An Ma, Niladri Chatterji, Xiang Cheng, Nicolas Flammarion, Peter Bartlett, and Michael I. Jordan · 1902
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A two-dimensional mapping with a strange attractor
Michel Hénon · 1976
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Diffusions hypercontractives
Dominique Bakry and Michel Émery · 1985
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Transportation cost for gaussian and other product measures
Michel Talagrand · 1996
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Exponential integrability and transportation cost related to logarithmic sobolev inequalities
S.G Bobkov and F Götze · 1998
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Generalization of an inequality by talagrand and links with the logarithmic sobolev inequality
Felix Otto and Cédric Villani · 2000
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On extensions of the brunn-minkowski and prékopa-leindler theorems, including inequalities for log concave functions, and with an application to the diffusion equation
Herm Jan Brascamp and Elliott H Lieb · 2002
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Polynomial approximations of symplectic dynamics and richness of chaos in non-hyperbolic area-preserving maps
Dmitry Turaev · 2002
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A convex/log-concave correlation inequality for Gaussian measure and an application to abstract Wiener spaces
Gilles Hargé · 2004
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Ordinary differential equations with applications
Carmen Chicone · 2006
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Coupling-based invertible neural networks are universal diffeomorphism approximators
Takeshi Teshima, Isao Ishikawa, Koichi Tojo, Kenta Oono, Masahiro Ikeda, and Masashi Sugiyama · 2006
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Exponentially stable nonlinear systems have polynomial lyapunov functions on bounded regions, 2007
Matthew M. Peet · 2007
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Foundations of mechanics
Ralph Abraham and Jerrold E Marsden · 2008
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A first course on numerical methods
Uri M Ascher and Chen Greif · 2011
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Mass transportation and contractions
Alexander V Kolesnikov · 2011
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The geometry of the group of symplectic diffeomorphism
Leonid Polterovich · 2012
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Analysis and geometry of Markov diffusion operators , volume 348
Dominique Bakry, Ivan Gentil, and Michel Ledoux · 2013
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Nice: Non-linear independent components estimation
Laurent Dinh, David Krueger, and Yoshua Bengio · 2014
Glow: Generative flow with invertible 1x1 convolutions
Durk P Kingma and Prafulla Dhariwal · 2018
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High-dimensional probability: An introduction with applications in data science , volume 47
Roman Vershynin · 2018
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Augmented neural odes
Emilien Dupont, Arnaud Doucet, and Yee Whye Teh · 2019
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Sum-of-squares polynomial flow, 2019
Priyank Jaini, Kira A. Selby, and Yaoliang Yu · 2019
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Generative modeling by estimating gradients of the data distribution
Yang Song and Stefano Ermon · 2019
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Accelerated flow for probability distributions
Amirhossein Taghvaei and Prashant Mehta · 2019
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Stochastic processes and applications: diffusion processes, the Fokker-Planck and Langevin equations , volume 60
Grigorios A Pavliotis · 2014
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Log-concavity and strong log-concavity: a review
Adrien Saumard and Jon A Wellner · 2014
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Variational inference with normalizing flows
Danilo Rezende and Shakir Mohamed · 2015
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Density estimation using real nvp
Laurent Dinh, Jascha Sohl-Dickstein, and Samy Bengio · 2016
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Jens Behrmann, Will Grathwohl, Ricky TQ Chen, David Duvenaud, and Jörn-Henrik Jacobsen · 2018
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Ffjord: Free-form continuous dynamics for scalable reversible generative models
Will Grathwohl, Ricky TQ Chen, Jesse Bettencourt, Ilya Sutskever, and David Duvenaud · 2018
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Augmented normalizing flows: Bridging the gap between generative flows and latent variable models
Chin-Wei Huang, Laurent Dinh, and Aaron Courville · 2020
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Representational aspects of depth and conditioning in normalizing flows, 2020
Frederic Koehler, Viraj Mehta, and Andrej Risteski · 2020
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Gaussianization flows, 2020
Chenlin Meng, Yang Song, Jiaming Song, and Stefano Ermon · 2020
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Score-based generative modeling through stochastic differential equations
Yang Song, Jascha Sohl-Dickstein, Diederik P Kingma, Abhishek Kumar, Stefano Ermon, and Ben Poole · 2020
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Approximation capabilities of neural odes and invertible residual networks
Han Zhang, Xi Gao, Jacob Unterman, and Tom Arodz · 2020
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