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Categorical Reparameterization with Gumbel-Softmax
v1v2v3v4v5 (latest)

Categorical Reparameterization with Gumbel-Softmax

3 November 2016
Eric Jang
S. Gu
Ben Poole
    BDL
ArXiv (abs)PDFHTML

Papers citing "Categorical Reparameterization with Gumbel-Softmax"

50 / 3,025 papers shown
Title
Cause-Effect Deep Information Bottleneck For Systematically Missing
  Covariates
Cause-Effect Deep Information Bottleneck For Systematically Missing Covariates
S. Parbhoo
Mario Wieser
Aleksander Wieczorek
Volker Roth
CML
85
5
0
06 Jul 2018
New Losses for Generative Adversarial Learning
Victor Berger
Michèle Sebag
GAN
47
0
0
03 Jul 2018
Generating Multi-Categorical Samples with Generative Adversarial
  Networks
Generating Multi-Categorical Samples with Generative Adversarial Networks
R. Camino
Christian A. Hammerschmidt
R. State
SyDaGAN
48
71
0
03 Jul 2018
Stochastic Layer-Wise Precision in Deep Neural Networks
Stochastic Layer-Wise Precision in Deep Neural Networks
Griffin Lacey
Graham W. Taylor
S. Areibi
86
18
0
03 Jul 2018
Guided evolutionary strategies: Augmenting random search with surrogate
  gradients
Guided evolutionary strategies: Augmenting random search with surrogate gradients
Niru Maheswaranathan
Luke Metz
George Tucker
Dami Choi
Jascha Narain Sohl-Dickstein
76
20
0
26 Jun 2018
Deep $k$-Means: Jointly clustering with $k$-Means and learning
  representations
Deep kkk-Means: Jointly clustering with kkk-Means and learning representations
Maziar Moradi Fard
Thibaut Thonet
Éric Gaussier
84
239
0
26 Jun 2018
Hierarchical VampPrior Variational Fair Auto-Encoder
Hierarchical VampPrior Variational Fair Auto-Encoder
P. Botros
Jakub M. Tomczak
DRL
69
7
0
26 Jun 2018
Tensor Monte Carlo: particle methods for the GPU era
Tensor Monte Carlo: particle methods for the GPU era
Laurence Aitchison
BDLDRL
85
13
0
22 Jun 2018
Learning K-way D-dimensional Discrete Codes for Compact Embedding
  Representations
Learning K-way D-dimensional Discrete Codes for Compact Embedding Representations
Ting-Li Chen
Martin Renqiang Min
Yizhou Sun
77
71
0
21 Jun 2018
InfoCatVAE: Representation Learning with Categorical Variational
  Autoencoders
InfoCatVAE: Representation Learning with Categorical Variational Autoencoders
Edouard Pineau
Marc Lelarge
DRL
83
13
0
20 Jun 2018
Deep Neural Decision Trees
Deep Neural Decision Trees
Yongxin Yang
Irene Garcia Morillo
Timothy M. Hospedales
PINN
65
187
0
19 Jun 2018
Nonparametric Topic Modeling with Neural Inference
Nonparametric Topic Modeling with Neural Inference
Xuefei Ning
Yin Zheng
Zhuxi Jiang
Yu Wang
Huazhong Yang
Junzhou Huang
BDL
79
19
0
18 Jun 2018
On Machine Learning and Structure for Mobile Robots
On Machine Learning and Structure for Mobile Robots
Markus Wulfmeier
44
6
0
15 Jun 2018
On Accurate Evaluation of GANs for Language Generation
On Accurate Evaluation of GANs for Language Generation
Stanislau Semeniuta
Aliaksei Severyn
Sylvain Gelly
EGVM
65
81
0
13 Jun 2018
Gaussian mixture models with Wasserstein distance
Gaussian mixture models with Wasserstein distance
Benoit Gaujac
Ilya Feige
David Barber
48
9
0
12 Jun 2018
Sparse Stochastic Zeroth-Order Optimization with an Application to
  Bandit Structured Prediction
Sparse Stochastic Zeroth-Order Optimization with an Application to Bandit Structured Prediction
Artem Sokolov
Julian Hitschler
Mayumi Ohta
Stefan Riezler
47
7
0
12 Jun 2018
Generative Adversarial Nets for Information Retrieval: Fundamentals and
  Advances
Generative Adversarial Nets for Information Retrieval: Fundamentals and Advances
Weinan Zhang
GAN
33
11
0
10 Jun 2018
Towards Binary-Valued Gates for Robust LSTM Training
Towards Binary-Valued Gates for Robust LSTM Training
Zhuohan Li
Di He
Fei Tian
Wei-neng Chen
Tao Qin
Liwei Wang
Tie-Yan Liu
MQ
59
47
0
08 Jun 2018
Pathwise Derivatives for Multivariate Distributions
Pathwise Derivatives for Multivariate Distributions
M. Jankowiak
Theofanis Karaletsos
128
11
0
05 Jun 2018
Latent Tree Learning with Differentiable Parsers: Shift-Reduce Parsing
  and Chart Parsing
Latent Tree Learning with Differentiable Parsers: Shift-Reduce Parsing and Chart Parsing
Jean Maillard
S. Clark
56
18
0
03 Jun 2018
Reparameterization Gradient for Non-differentiable Models
Reparameterization Gradient for Non-differentiable Models
Wonyeol Lee
Hangyeol Yu
Hongseok Yang
DRL
139
32
0
01 Jun 2018
Fast, Diverse and Accurate Image Captioning Guided By Part-of-Speech
Fast, Diverse and Accurate Image Captioning Guided By Part-of-Speech
Aditya Deshpande
J. Aneja
Liwei Wang
Alex Schwing
David A. Forsyth
103
148
0
31 May 2018
Greedy Attack and Gumbel Attack: Generating Adversarial Examples for
  Discrete Data
Greedy Attack and Gumbel Attack: Generating Adversarial Examples for Discrete Data
Puyudi Yang
Jianbo Chen
Cho-Jui Hsieh
Jane-ling Wang
Michael I. Jordan
AAMLSILM
108
116
0
31 May 2018
Conformation Clustering of Long MD Protein Dynamics with an Adversarial
  Autoencoder
Conformation Clustering of Long MD Protein Dynamics with an Adversarial Autoencoder
Yunlong Liu
L. Amzel
14
1
0
31 May 2018
MolGAN: An implicit generative model for small molecular graphs
MolGAN: An implicit generative model for small molecular graphs
Nicola De Cao
Thomas Kipf
GNNGAN
216
936
0
30 May 2018
Unsupervised Text Style Transfer using Language Models as Discriminators
Unsupervised Text Style Transfer using Language Models as Discriminators
Zichao Yang
Zhiting Hu
Chris Dyer
Eric Xing
Taylor Berg-Kirkpatrick
106
273
0
30 May 2018
Theory and Experiments on Vector Quantized Autoencoders
Theory and Experiments on Vector Quantized Autoencoders
Aurko Roy
Ashish Vaswani
Arvind Neelakantan
Niki Parmar
91
88
0
28 May 2018
Discrete flow posteriors for variational inference in discrete dynamical
  systems
Discrete flow posteriors for variational inference in discrete dynamical systems
Laurence Aitchison
Vincent Adam
Srinivas C. Turaga
BDLDRL
51
4
0
28 May 2018
Inducing Grammars with and for Neural Machine Translation
Inducing Grammars with and for Neural Machine Translation
Ke M. Tran
Yonatan Bisk
55
22
0
28 May 2018
Revisiting Reweighted Wake-Sleep for Models with Stochastic Control Flow
Revisiting Reweighted Wake-Sleep for Models with Stochastic Control Flow
T. Le
Adam R. Kosiorek
N. Siddharth
Yee Whye Teh
Frank Wood
BDL
60
23
0
26 May 2018
Maximizing acquisition functions for Bayesian optimization
Maximizing acquisition functions for Bayesian optimization
James T. Wilson
Frank Hutter
M. Deisenroth
157
250
0
25 May 2018
Fairness GAN
Fairness GAN
P. Sattigeri
Samuel C. Hoffman
Vijil Chenthamarakshan
Kush R. Varshney
133
93
0
24 May 2018
Amortized Context Vector Inference for Sequence-to-Sequence Networks
Amortized Context Vector Inference for Sequence-to-Sequence Networks
S. Chatzis
Aristotelis Charalampous
Kyriacos Tolias
24
0
0
23 May 2018
Implicit Reparameterization Gradients
Implicit Reparameterization Gradients
Michael Figurnov
S. Mohamed
A. Mnih
BDL
149
235
0
22 May 2018
Learning to Teach in Cooperative Multiagent Reinforcement Learning
Learning to Teach in Cooperative Multiagent Reinforcement Learning
Shayegan Omidshafiei
Dong-Ki Kim
Miao Liu
Gerald Tesauro
Matthew D Riemer
Chris Amato
Murray Campbell
Jonathan P. How
69
136
0
20 May 2018
Learning compositionally through attentive guidance
Learning compositionally through attentive guidance
Dieuwke Hupkes
Anand Singh
K. Korrel
Germán Kruszewski
Elia Bruni
CoGe
68
30
0
20 May 2018
Learning Graph-Level Representations with Recurrent Neural Networks
Learning Graph-Level Representations with Recurrent Neural Networks
Yu Jin
Joseph Jaja
GNNSSL
81
13
0
20 May 2018
Learning to Repair Software Vulnerabilities with Generative Adversarial
  Networks
Learning to Repair Software Vulnerabilities with Generative Adversarial Networks
Jacob A. Harer
Onur Ozdemir
Tomo Lazovich
Christopher P. Reale
Rebecca L. Russell
Louis Y. Kim
Peter Chin
GAN
90
73
0
18 May 2018
DVAE#: Discrete Variational Autoencoders with Relaxed Boltzmann Priors
DVAE#: Discrete Variational Autoencoders with Relaxed Boltzmann Priors
Arash Vahdat
Evgeny Andriyash
W. Macready
104
49
0
18 May 2018
GumBolt: Extending Gumbel trick to Boltzmann priors
GumBolt: Extending Gumbel trick to Boltzmann priors
Amir Khoshaman
Mohammad H. Amin
71
14
0
18 May 2018
Learning Permutations with Sinkhorn Policy Gradient
Learning Permutations with Sinkhorn Policy Gradient
Patrick Emami
Sanjay Ranka
65
55
0
18 May 2018
NASH: Toward End-to-End Neural Architecture for Generative Semantic
  Hashing
NASH: Toward End-to-End Neural Architecture for Generative Semantic Hashing
Dinghan Shen
Qinliang Su
Paidamoyo Chapfuwa
Wenlin Wang
Guoyin Wang
Lawrence Carin
Ricardo Henao
74
58
0
14 May 2018
AMR Parsing as Graph Prediction with Latent Alignment
AMR Parsing as Graph Prediction with Latent Alignment
Chunchuan Lyu
Ivan Titov
GNNBDL
88
128
0
14 May 2018
Learning to Ask Questions in Open-domain Conversational Systems with
  Typed Decoders
Learning to Ask Questions in Open-domain Conversational Systems with Typed Decoders
Yansen Wang
Chenyi Liu
Minlie Huang
Liqiang Nie
BDL
93
83
0
13 May 2018
Backpropagating through Structured Argmax using a SPIGOT
Backpropagating through Structured Argmax using a SPIGOT
Hao Peng
Sam Thomson
Noah A. Smith
88
42
0
12 May 2018
Adversarial Contrastive Estimation
Adversarial Contrastive Estimation
A. Bose
Huan Ling
Yanshuai Cao
47
56
0
09 May 2018
MEGAN: Mixture of Experts of Generative Adversarial Networks for
  Multimodal Image Generation
MEGAN: Mixture of Experts of Generative Adversarial Networks for Multimodal Image Generation
D. Park
Seungjoo Yoo
Hyojin Bahng
Jaegul Choo
Noseong Park
GAN
47
24
0
07 May 2018
Sharp Attention Network via Adaptive Sampling for Person
  Re-identification
Sharp Attention Network via Adaptive Sampling for Person Re-identification
Chen Shen
Guo-Jun Qi
Rongxin Jiang
Zhongming Jin
Hongwei Yong
Yao-wu Chen
Xiansheng Hua
110
38
0
07 May 2018
Pixel-wise Attentional Gating for Parsimonious Pixel Labeling
Pixel-wise Attentional Gating for Parsimonious Pixel Labeling
Shu Kong
Charless C. Fowlkes
99
40
0
03 May 2018
Generalising Cost-Optimal Particle Filtering
Generalising Cost-Optimal Particle Filtering
Andrew Warrington
Neil Dhir
8
1
0
02 May 2018
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