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A Review of the Gumbel-max Trick and its Extensions for Discrete Stochasticity in Machine Learning

A Review of the Gumbel-max Trick and its Extensions for Discrete Stochasticity in Machine Learning

Iris A. M. Huijben
W. Kool
Max B. Paulus
Ruud J. G. van Sloun
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Papers citing "A Review of the Gumbel-max Trick and its Extensions for Discrete Stochasticity in Machine Learning"

3 / 103 papers shown
Title
On Sampling from the Gibbs Distribution with Random Maximum A-Posteriori Perturbations
On Sampling from the Gibbs Distribution with Random Maximum A-Posteriori Perturbations
Tamir Hazan
Subhransu Maji
Tommi Jaakkola
64
56
0
29 Sep 2013
Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation
Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation
Yoshua Bengio
Nicholas Léonard
Aaron Courville
381
3,129
0
15 Aug 2013
Fixed-Form Variational Posterior Approximation through Stochastic Linear Regression
Fixed-Form Variational Posterior Approximation through Stochastic Linear Regression
Tim Salimans
David A. Knowles
113
252
0
28 Jun 2012