Fetching the paper…
Reading the bibliography…
The Gumbel-Softmax is a continuous distribution over the simplex that is often used as a relaxation of discrete distributions.
A stochastic approximation method
H. Robbins and S. Monro · 1951
Earlier work this paper cites.
A bayesian analysis of some nonparametric problems
T. S. Ferguson · 1973
Earlier work this paper cites.
Likelihood ratio gradient estimation for stochastic systems
P. W. Glynn · 1990
Earlier work this paper cites.
Simple statistical gradient-following algorithms for connectionist reinforcement learning
R. J. Williams · 1992
Earlier work this paper cites.
Stochastic gradient descent tricks
L. Bottou · 2012
Earlier work this paper cites.
Estimating or propagating gradients through stochastic neurons for conditional computation
Y. Bengio, N. Léonard, and A. Courville · 2013
Earlier work this paper cites.
Auto-encoding variational bayes
D. P. Kingma and M. Welling · 2014
Earlier work this paper cites.
Techniques for learning binary stochastic feedforward neural networks, 2014
T. Raiko, M. Berglund, G. Alain, and L. Dinh · 2014
Earlier work this paper cites.
Stochastic backpropagation and approximate inference in deep generative models
D. J. Rezende, S. Mohamed, and D. Wierstra · 2014
Earlier work this paper cites.
Importance weighted autoencoders
Y. Burda, R. Grosse, and R. Salakhutdinov · 2015
Earlier work this paper cites.
Muprop: Unbiased backpropagation for stochastic neural networks
S. Gu, S. Levine, I. Sutskever, and A. Mnih · 2015
Earlier work this paper cites.
Variational inference with normalizing flows
D. Rezende and S. Mohamed · 2015
Cited alongside, same era.
Composing graphical models with neural networks for structured representations and fast inference
M. Johnson, D. K. Duvenaud, A. Wiltschko, R. P. Adams, and S. R. Datta · 2016
Cited alongside, same era.
Improved variational inference with inverse autoregressive flow
D. P. Kingma, T. Salimans, R. Jozefowicz, X. Chen, I. Sutskever, and M. Welling · 2016
Cited alongside, same era.
Gans for sequences of discrete elements with the gumbel-softmax distribution
M. J. Kusner and J. M. Hernández-Lobato · 2016
Cited alongside, same era.
Approximate inference for deep latent gaussian mixtures
E. Nalisnick, L. Hertel, and P. Smyth · 2016
Cited alongside, same era.
Lost relatives of the gumbel trick
Stick-breaking variational autoencoders
E. Nalisnick and P. Smyth · 2017
Later among the works it cites.
Sticking the landing: Simple, lower-variance gradient estimators for variational inference
G. Roeder, Y. Wu, and D. K. Duvenaud · 2017
Later among the works it cites.
Rebar: Low-variance, unbiased gradient estimates for discrete latent variable models
G. Tucker, A. Mnih, C. J. Maddison, J. Lawson, and J. Sohl-Dickstein · 2017
Later among the works it cites.
Learning disentangled joint continuous and discrete representations
E. Dupont · 2018
Later among the works it cites.
Backpropagation through the void: Optimizing control variates for black-box gradient estimation
W. Grathwohl, D. Choi, Y. Wu, G. Roeder, and D. Duvenaud · 2018
Later among the works it cites.
Reparameterizing the birkhoff polytope for variational permutation inference
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
M. Balog, N. Tripuraneni, Z. Ghahramani, and A. Weller · 2017
Cited alongside, same era.
Density estimation using real nvp
L. Dinh, J. Sohl-Dickstein, and S. Bengio · 2017
Cited alongside, same era.
Categorical reparameterization with gumbel-softmax
E. Jang, S. Gu, and B. Poole · 2017
Cited alongside, same era.
The concrete distribution: A continuous relaxation of discrete random variables
C. J. Maddison, A. Mnih, and Y. W. Teh · 2017
Cited alongside, same era.
Reducing reparameterization gradient variance
A. Miller, N. Foti, A. D’Amour, and R. P. Adams · 2017
Cited alongside, same era.
Variational inference for monte carlo objectives
A. Mnih and D. Rezende
Cited in the paper.
Variational inference for monte carlo objectives
A. Mnih and D. J. Rezende
Cited in the paper.
S. Linderman, G. Mena, H. Cooper, L. Paninski, and J. Cunningham · 2018
Later among the works it cites.
A new distribution on the simplex with auto-encoding applications
A. Stirn, T. Jebara, and D. Knowles · 2019
Closest in time.
Reparameterizable subset sampling via continuous relaxations
S. M. Xie and S. Ermon · 2019
Closest in time.
The continuous categorical: a novel simplex-valued exponential family
E. Gordon-Rodriguez, G. Loaiza-Ganem, and J. P. Cunningham · 2020
Closest in time.
Estimating gradients for discrete random variables by sampling without replacement
W. Kool, H. van Hoof, and M. Welling · 2020
Closest in time.