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Monotonic neural networks have recently been proposed as a way to define invertible transformations.
Application of the back propagation neural network algorithm with monotonicity constraints for two-group classification problems
N. P. Archer and S. Wang · 1993
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Monotonic networks
J. Sill · 1998
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Monotone and partially monotone neural networks
H. Daniels and M. Velikova · 2010
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Auto-encoding variational bayes
D. P. Kingma and M. Welling · 2013
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Nice: Non-linear independent components estimation
L. Dinh, D. Krueger, and Y. Bengio · 2015
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Made: Masked autoencoder for distribution estimation
M. Germain, K. Gregor, I. Murray, and H. Larochelle · 2015
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Variational inference with normalizing flows
D. Rezende and S. Mohamed · 2015
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Monotonic calibrated interpolated look-up tables
M. Gupta, A. Cotter, J. Pfeifer, K. Voevodski, K. Canini, A. Mangylov, W. Moczydlowski, and A. Van Esbroeck · 2016
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Improved variational inference with inverse autoregressive flow
D. P. Kingma, T. Salimans, R. Jozefowicz, X. Chen, I. Sutskever, and M. Welling · 2016
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Wavenet: A generative model for raw audio
A. van den Oord, S. Dieleman, H. Zen, K. Simonyan, O. Vinyals, A. Graves, N. Kalchbrenner, A. Senior, and K. Kavukcuoglu · 2016
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Density estimation using real nvp
L. Dinh, J. Sohl-Dickstein, and S. Bengio · 2017
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Hypernetworks
D. Ha, A. M. Dai, and Q. V. Le · 2017
Cited alongside, same era.
Masked autoregressive flow for density estimation
G. Papamakarios, T. Pavlakou, and I. Murray · 2017
Cited alongside, same era.
Deep probabilistic programming
D. Tran, M. D. Hoffman, R. A. Saurous, E. Brevdo, K. Murphy, and D. M. Blei · 2017
Cited alongside, same era.
Deep lattice networks and partial monotonic functions
S. You, D. Ding, K. Canini, J. Pfeifer, and M. Gupta · 2017
Cited alongside, same era.
Ffjord: Free-form continuous dynamics for scalable reversible generative models
W. Grathwohl, R. T. Chen, J. Bettencourt, I. Sutskever, and D. Duvenaud · 2018
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Neural autoregressive flows
C.-W. Huang, D. Krueger, A. Lacoste, and A. Courville · 2018
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Glow: Generative flow with invertible 1x1 convolutions
D. P. Kingma and P. Dhariwal · 2018
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Transformation autoregressive networks
J. Oliva, A. Dubey, M. Zaheer, B. Poczos, R. Salakhutdinov, E. Xing, and J. Schneider · 2018
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Parallel wavenet: Fast high-fidelity speech synthesis
A. Oord, Y. Li, I. Babuschkin, K. Simonyan, O. Vinyals, K. Kavukcuoglu, G. Driessche, E. Lockhart, L. Cobo, F. Stimberg, et al · 2018
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R. v. d. Berg, L. Hasenclever, J. M. Tomczak, and M. Welling · 2018
Cited alongside, same era.
Neural ordinary differential equations
T. Q. Chen, Y. Rubanova, J. Bettencourt, and D. K. Duvenaud · 2018
Cited alongside, same era.
Regularisation of neural networks by enforcing lipschitz continuity
H. Gouk, E. Frank, B. Pfahringer, and M. Cree · 2018
Cited alongside, same era.
N. De Cao, I. Titov, and W. Aziz · 2019
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Sum-of-squares polynomial flow
P. Jaini, K. A. Selby, and Y. Yu · 2019
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Sequential neural likelihood: Fast likelihood-free inference with autoregressive flows
G. Papamakarios, D. C. Sterratt, and I. Murray · 2019
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