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DVAE++: Discrete Variational Autoencoders with Overlapping
  Transformations

DVAE++: Discrete Variational Autoencoders with Overlapping Transformations

14 February 2018
Arash Vahdat
W. Macready
Zhengbing Bian
Amir Khoshaman
Evgeny Andriyash
ArXivPDFHTML

Papers citing "DVAE++: Discrete Variational Autoencoders with Overlapping Transformations"

30 / 30 papers shown
Title
MoFM: A Large-Scale Human Motion Foundation Model
MoFM: A Large-Scale Human Motion Foundation Model
Mohammadreza Baharani
Ghazal Alinezhad Noghre
Armin Danesh Pazho
Gabriel Maldonado
Hamed Tabkhi
AI4CE
329
1
0
08 Feb 2025
Squeeze-and-Excitation Networks
Squeeze-and-Excitation Networks
Jie Hu
Li Shen
Samuel Albanie
Gang Sun
Enhua Wu
263
26,241
0
05 Sep 2017
Self-Normalizing Neural Networks
Self-Normalizing Neural Networks
Günter Klambauer
Thomas Unterthiner
Andreas Mayr
Sepp Hochreiter
165
2,496
0
08 Jun 2017
VAE with a VampPrior
VAE with a VampPrior
Jakub M. Tomczak
Max Welling
GAN
BDL
47
628
0
19 May 2017
Semi-Supervised Generation with Cluster-aware Generative Models
Semi-Supervised Generation with Cluster-aware Generative Models
Lars Maaløe
Marco Fraccaro
Ole Winther
85
28
0
03 Apr 2017
REBAR: Low-variance, unbiased gradient estimates for discrete latent
  variable models
REBAR: Low-variance, unbiased gradient estimates for discrete latent variable models
George Tucker
A. Mnih
Chris J. Maddison
John Lawson
Jascha Narain Sohl-Dickstein
BDL
138
282
0
21 Mar 2017
Parallel Multiscale Autoregressive Density Estimation
Parallel Multiscale Autoregressive Density Estimation
Scott E. Reed
Aaron van den Oord
Nal Kalchbrenner
Sergio Gomez Colmenarejo
Ziyun Wang
Dan Belov
Nando de Freitas
BDL
55
204
0
10 Mar 2017
PixelCNN++: Improving the PixelCNN with Discretized Logistic Mixture
  Likelihood and Other Modifications
PixelCNN++: Improving the PixelCNN with Discretized Logistic Mixture Likelihood and Other Modifications
Tim Salimans
A. Karpathy
Xi Chen
Diederik P. Kingma
34
933
0
19 Jan 2017
Variational Lossy Autoencoder
Variational Lossy Autoencoder
Xi Chen
Diederik P. Kingma
Tim Salimans
Yan Duan
Prafulla Dhariwal
John Schulman
Ilya Sutskever
Pieter Abbeel
DRL
SSL
GAN
99
672
0
08 Nov 2016
Categorical Reparameterization with Gumbel-Softmax
Categorical Reparameterization with Gumbel-Softmax
Eric Jang
S. Gu
Ben Poole
BDL
182
5,323
0
03 Nov 2016
The Concrete Distribution: A Continuous Relaxation of Discrete Random
  Variables
The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables
Chris J. Maddison
A. Mnih
Yee Whye Teh
BDL
71
2,518
0
02 Nov 2016
Discrete Variational Autoencoders
Discrete Variational Autoencoders
J. Rolfe
BDL
DRL
112
255
0
07 Sep 2016
Hierarchical Multiscale Recurrent Neural Networks
Hierarchical Multiscale Recurrent Neural Networks
Junyoung Chung
Sungjin Ahn
Yoshua Bengio
BDL
57
534
0
06 Sep 2016
Improving Variational Inference with Inverse Autoregressive Flow
Improving Variational Inference with Inverse Autoregressive Flow
Diederik P. Kingma
Tim Salimans
Rafal Jozefowicz
Xi Chen
Ilya Sutskever
Max Welling
BDL
DRL
72
1,805
0
15 Jun 2016
Variational inference for Monte Carlo objectives
Variational inference for Monte Carlo objectives
A. Mnih
Danilo Jimenez Rezende
DRL
BDL
81
289
0
22 Feb 2016
Ladder Variational Autoencoders
Ladder Variational Autoencoders
C. Sønderby
T. Raiko
Lars Maaløe
Søren Kaae Sønderby
Ole Winther
BDL
DRL
59
907
0
06 Feb 2016
Pixel Recurrent Neural Networks
Pixel Recurrent Neural Networks
Aaron van den Oord
Nal Kalchbrenner
Koray Kavukcuoglu
SSeg
GAN
343
2,563
0
25 Jan 2016
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
932
192,638
0
10 Dec 2015
Fast and Accurate Deep Network Learning by Exponential Linear Units
  (ELUs)
Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs)
Djork-Arné Clevert
Thomas Unterthiner
Sepp Hochreiter
169
5,502
0
23 Nov 2015
Generating Sentences from a Continuous Space
Generating Sentences from a Continuous Space
Samuel R. Bowman
Luke Vilnis
Oriol Vinyals
Andrew M. Dai
Rafal Jozefowicz
Samy Bengio
DRL
56
2,352
0
19 Nov 2015
MuProp: Unbiased Backpropagation for Stochastic Neural Networks
MuProp: Unbiased Backpropagation for Stochastic Neural Networks
S. Gu
Sergey Levine
Ilya Sutskever
A. Mnih
BDL
29
143
0
16 Nov 2015
Importance Weighted Autoencoders
Importance Weighted Autoencoders
Yuri Burda
Roger C. Grosse
Ruslan Salakhutdinov
BDL
185
1,240
0
01 Sep 2015
Deep Generative Image Models using a Laplacian Pyramid of Adversarial
  Networks
Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks
Emily L. Denton
Soumith Chintala
Arthur Szlam
Rob Fergus
GAN
64
2,241
0
18 Jun 2015
Batch Normalization: Accelerating Deep Network Training by Reducing
  Internal Covariate Shift
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
Sergey Ioffe
Christian Szegedy
OOD
194
43,154
0
11 Feb 2015
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
351
149,474
0
22 Dec 2014
Semi-Supervised Learning with Deep Generative Models
Semi-Supervised Learning with Deep Generative Models
Diederik P. Kingma
Danilo Jimenez Rezende
S. Mohamed
Max Welling
GAN
SSL
BDL
42
2,731
0
20 Jun 2014
Neural Variational Inference and Learning in Belief Networks
Neural Variational Inference and Learning in Belief Networks
A. Mnih
Karol Gregor
BDL
56
727
0
31 Jan 2014
Auto-Encoding Variational Bayes
Auto-Encoding Variational Bayes
Diederik P. Kingma
Max Welling
BDL
308
16,972
0
20 Dec 2013
Deep AutoRegressive Networks
Deep AutoRegressive Networks
Karol Gregor
Ivo Danihelka
A. Mnih
Charles Blundell
Daan Wierstra
AI4TS
BDL
53
281
0
31 Oct 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
254
3,099
0
15 Aug 2013
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