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Flows are exact-likelihood generative neural networks that transform samples from a simple prior distribution to the samples of the probability distribution of interest.
Nice: Nonlinear independent components estimation
L. Dinh, D. Krueger, and Y. Bengio · 2015
Earlier work this paper cites.
Variational inference with normalizing flows
D. J. Rezende and S. Mohamed · 2015
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Density estimation using real nvp
Laurent Dinh, Jascha Sohl-Dickstein, and Samy Bengio · 2016
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Improved variational inference with inverse autoregressive flow
Durk P Kingma, Tim Salimans, Rafal Jozefowicz, Xi Chen, Ilya Sutskever, and Max Welling · 2016
Earlier work this paper cites.
Masked autoregressive flow for density estimation
George Papamakarios, Theo Pavlakou, and Iain Murray · 2017
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Jens Behrmann, David Duvenaud, and Jörn-Henrik Jacobsen · 2018
Earlier work this paper cites.
Neural ordinary differential equations
Tian Qi Chen, Yulia Rubanova, Jesse Bettencourt, and David K Duvenaud · 2018
Cited alongside, same era.
Ffjord: Free-form continuous dynamics for scalable reversible generative models
Will Grathwohl, Ricky TQ Chen, Jesse Betterncourt, Ilya Sutskever, and David Duvenaud · 2018
Cited alongside, same era.
Glow: Generative flow with invertible 1x1 convolutions
Durk P Kingma and Prafulla Dhariwal · 2018
Cited alongside, same era.
Parallel WaveNet: Fast High-Fidelity Speech Synthesis
A. van den Oord, Y. Li, I. Babuschkin, K. Simonyan, O. Vinyals, K. Kavukcuoglu, G. van den Driessche, E. Lockhart, L. C. Cobo, F. Stimberg, N. Casagrande, D. Grewe, S. Noury, S. Dieleman, E. Elsen, N. Kalchbrenner, H. Zen, A. Graves, H. King, T. Walters, D. Belov, and D. Hassabis · 2018
Cited alongside, same era.
Flow-based generative models for markov chain monte carlo in lattice field theory
Conor Durkan, Artur Bekasov, Iain Murray, and George Papamakarios · 2019
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Jonathan Ho, Xi Chen, Aravind Srinivas, Yan Duan, and Pieter Abbeel · 2019
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Flownet3d: Learning scene flow in 3d point clouds
Xingyu Liu, Charles R. Qi, and Leonidas J. Guibas · 2019
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Boltzmann generators-sampling equilibrium states of many-body systems with deep learning
Frank Noé, Simon Olsson, Jonas Köhler, and Hao Wu · 2019
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Deep autoregressive models for the efficient variational simulation of many-body quantum systems
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MS Albergo, G Kanwar, and PE Shanahan · 2019
Cited alongside, same era.
Or Sharir, Yoav Levine, Noam Wies, Giuseppe Carleo, and Amnon Shashua · 2019
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