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Learning Discrete and Continuous Factors of Data via Alternating
  Disentanglement

Learning Discrete and Continuous Factors of Data via Alternating Disentanglement

23 May 2019
Yeonwoo Jeong
Hyun Oh Song
ArXivPDFHTML

Papers citing "Learning Discrete and Continuous Factors of Data via Alternating Disentanglement"

15 / 15 papers shown
Title
Efficient end-to-end learning for quantizable representations
Efficient end-to-end learning for quantizable representations
Yeonwoo Jeong
Hyun Oh Song
MQ
39
11
0
15 May 2018
Understanding disentangling in $β$-VAE
Understanding disentangling in βββ-VAE
Christopher P. Burgess
I. Higgins
Arka Pal
Loic Matthey
Nicholas Watters
Guillaume Desjardins
Alexander Lerchner
CoGe
DRL
57
829
0
10 Apr 2018
Learning Disentangled Joint Continuous and Discrete Representations
Learning Disentangled Joint Continuous and Discrete Representations
Emilien Dupont
DRL
76
242
0
31 Mar 2018
Disentangling by Factorising
Disentangling by Factorising
Hyunjik Kim
A. Mnih
CoGe
OOD
62
1,346
0
16 Feb 2018
Auto-Encoding Total Correlation Explanation
Auto-Encoding Total Correlation Explanation
Shuyang Gao
Rob Brekelmans
Greg Ver Steeg
Aram Galstyan
BDL
DRL
66
78
0
16 Feb 2018
Neural Discrete Representation Learning
Neural Discrete Representation Learning
Aaron van den Oord
Oriol Vinyals
Koray Kavukcuoglu
BDL
SSL
OCL
210
4,989
0
02 Nov 2017
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning
  Algorithms
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms
Han Xiao
Kashif Rasul
Roland Vollgraf
260
8,876
0
25 Aug 2017
Categorical Reparameterization with Gumbel-Softmax
Categorical Reparameterization with Gumbel-Softmax
Eric Jang
S. Gu
Ben Poole
BDL
297
5,364
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
171
2,529
0
02 Nov 2016
InfoGAN: Interpretable Representation Learning by Information Maximizing
  Generative Adversarial Nets
InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets
Xi Chen
Yan Duan
Rein Houthooft
John Schulman
Ilya Sutskever
Pieter Abbeel
GAN
157
4,232
0
12 Jun 2016
Variational inference for Monte Carlo objectives
Variational inference for Monte Carlo objectives
A. Mnih
Danilo Jimenez Rezende
DRL
BDL
153
290
0
22 Feb 2016
Adversarial Autoencoders
Adversarial Autoencoders
Alireza Makhzani
Jonathon Shlens
Navdeep Jaitly
Ian Goodfellow
Brendan J. Frey
GAN
86
2,223
0
18 Nov 2015
Neural Variational Inference and Learning in Belief Networks
Neural Variational Inference and Learning in Belief Networks
A. Mnih
Karol Gregor
BDL
167
729
0
31 Jan 2014
Auto-Encoding Variational Bayes
Auto-Encoding Variational Bayes
Diederik P. Kingma
Max Welling
BDL
433
16,944
0
20 Dec 2013
Representation Learning: A Review and New Perspectives
Representation Learning: A Review and New Perspectives
Yoshua Bengio
Aaron Courville
Pascal Vincent
OOD
SSL
243
12,422
0
24 Jun 2012
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