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Auto-Encoding Variational Bayes

Auto-Encoding Variational Bayes

20 December 2013
Diederik P. Kingma
Max Welling
    BDL
ArXivPDFHTML

Papers citing "Auto-Encoding Variational Bayes"

50 / 3,208 papers shown
Title
Semi-Supervised Learning with Context-Conditional Generative Adversarial
  Networks
Semi-Supervised Learning with Context-Conditional Generative Adversarial Networks
Emily L. Denton
Sam Gross
Rob Fergus
GAN
27
150
0
19 Nov 2016
Associative Adversarial Networks
Associative Adversarial Networks
Tarik Arici
Asli Celikyilmaz
GAN
34
17
0
18 Nov 2016
Fast Non-Parametric Tests of Relative Dependency and Similarity
Fast Non-Parametric Tests of Relative Dependency and Similarity
Wacha Bounliphone
Eugene Belilovsky
A. Tenenhaus
Ioannis Antonoglou
Arthur Gretton
Matthew B. Blashcko
31
1
0
17 Nov 2016
Semantic Regularisation for Recurrent Image Annotation
Semantic Regularisation for Recurrent Image Annotation
Feng Liu
Tao Xiang
Timothy M. Hospedales
Wankou Yang
Changyin Sun
34
103
0
16 Nov 2016
Deep Variational Inference Without Pixel-Wise Reconstruction
Deep Variational Inference Without Pixel-Wise Reconstruction
Siddharth Agrawal
Ambedkar Dukkipati
DRL
3DV
BDL
30
13
0
16 Nov 2016
Variational Deep Embedding: An Unsupervised and Generative Approach to
  Clustering
Variational Deep Embedding: An Unsupervised and Generative Approach to Clustering
Zhuxi Jiang
Yin Zheng
Huachun Tan
Bangsheng Tang
Hanning Zhou
BDL
DRL
24
723
0
16 Nov 2016
On the Quantitative Analysis of Decoder-Based Generative Models
On the Quantitative Analysis of Decoder-Based Generative Models
Yuhuai Wu
Yuri Burda
Ruslan Salakhutdinov
Roger C. Grosse
GAN
22
223
0
14 Nov 2016
Least Squares Generative Adversarial Networks
Least Squares Generative Adversarial Networks
Xudong Mao
Qing Li
Haoran Xie
Raymond Y. K. Lau
Zhen Wang
Stephen Paul Smolley
GAN
127
4,535
0
13 Nov 2016
Disentangling factors of variation in deep representations using
  adversarial training
Disentangling factors of variation in deep representations using adversarial training
Michaël Mathieu
Jun Zhao
Pablo Sprechmann
Aditya A. Ramesh
Yann LeCun
DRL
CML
53
489
0
10 Nov 2016
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
47
671
0
08 Nov 2016
Unrolled Generative Adversarial Networks
Unrolled Generative Adversarial Networks
Luke Metz
Ben Poole
David Pfau
Jascha Narain Sohl-Dickstein
GAN
59
1,001
0
07 Nov 2016
DeepCoder: Learning to Write Programs
DeepCoder: Learning to Write Programs
Matej Balog
Alexander L. Gaunt
Marc Brockschmidt
Sebastian Nowozin
Daniel Tarlow
AIMat
NAI
24
566
0
07 Nov 2016
Joint Multimodal Learning with Deep Generative Models
Joint Multimodal Learning with Deep Generative Models
Masahiro Suzuki
Kotaro Nakayama
Y. Matsuo
DRL
GAN
35
222
0
07 Nov 2016
Learning to Draw Samples: With Application to Amortized MLE for
  Generative Adversarial Learning
Learning to Draw Samples: With Application to Amortized MLE for Generative Adversarial Learning
Dilin Wang
Qiang Liu
GAN
BDL
38
118
0
06 Nov 2016
TopicRNN: A Recurrent Neural Network with Long-Range Semantic Dependency
TopicRNN: A Recurrent Neural Network with Long-Range Semantic Dependency
Adji Bousso Dieng
Chong-Jun Wang
Jianfeng Gao
John Paisley
21
243
0
05 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
24
2,505
0
02 Nov 2016
Variational Inference via $χ$-Upper Bound Minimization
Variational Inference via χχχ-Upper Bound Minimization
Adji Bousso Dieng
Dustin Tran
Rajesh Ranganath
John Paisley
David M. Blei
BDL
81
36
0
01 Nov 2016
Inference Compilation and Universal Probabilistic Programming
Inference Compilation and Universal Probabilistic Programming
T. Le
A. G. Baydin
Frank Wood
UQCV
52
142
0
31 Oct 2016
Reparameterization Gradients through Acceptance-Rejection Sampling
  Algorithms
Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms
C. A. Naesseth
Francisco J. R. Ruiz
Scott W. Linderman
David M. Blei
BDL
25
107
0
18 Oct 2016
Deep Identity-aware Transfer of Facial Attributes
Deep Identity-aware Transfer of Facial Attributes
Mu Li
W. Zuo
David C. Zhang
CVBM
35
149
0
18 Oct 2016
AutoGP: Exploring the Capabilities and Limitations of Gaussian Process
  Models
AutoGP: Exploring the Capabilities and Limitations of Gaussian Process Models
K. Krauth
Edwin V. Bonilla
Kurt Cutajar
Maurizio Filippone
GP
BDL
16
54
0
18 Oct 2016
Learning and Transfer of Modulated Locomotor Controllers
Learning and Transfer of Modulated Locomotor Controllers
N. Heess
Greg Wayne
Yuval Tassa
Timothy Lillicrap
Martin Riedmiller
David Silver
24
207
0
17 Oct 2016
Amortised MAP Inference for Image Super-resolution
Amortised MAP Inference for Image Super-resolution
C. Sønderby
Jose Caballero
Lucas Theis
Wenzhe Shi
Ferenc Huszár
41
433
0
14 Oct 2016
Random Feature Expansions for Deep Gaussian Processes
Random Feature Expansions for Deep Gaussian Processes
Kurt Cutajar
Edwin V. Bonilla
Pietro Michiardi
Maurizio Filippone
BDL
14
142
0
14 Oct 2016
Voice Conversion from Non-parallel Corpora Using Variational
  Auto-encoder
Voice Conversion from Non-parallel Corpora Using Variational Auto-encoder
Chin-Cheng Hsu
Hsin-Te Hwang
Yi-Chiao Wu
Yu Tsao
H. Wang
34
299
0
13 Oct 2016
Learning What and Where to Draw
Learning What and Where to Draw
Scott E. Reed
Zeynep Akata
S. Mohan
Samuel Tenka
Bernt Schiele
Honglak Lee
DRL
GAN
30
618
0
08 Oct 2016
Automatic chemical design using a data-driven continuous representation
  of molecules
Automatic chemical design using a data-driven continuous representation of molecules
Rafael Gómez-Bombarelli
Jennifer N. Wei
David Duvenaud
José Miguel Hernández-Lobato
Benjamín Sánchez-Lengeling
Dennis Sheberla
J. Aguilera-Iparraguirre
Timothy D. Hirzel
Ryan P. Adams
Alán Aspuru-Guzik
3DV
76
2,889
0
07 Oct 2016
Neural Structural Correspondence Learning for Domain Adaptation
Neural Structural Correspondence Learning for Domain Adaptation
Yftah Ziser
Roi Reichart
DRL
16
107
0
05 Oct 2016
Deep Visual Foresight for Planning Robot Motion
Deep Visual Foresight for Planning Robot Motion
Chelsea Finn
Sergey Levine
35
777
0
03 Oct 2016
Structured Inference Networks for Nonlinear State Space Models
Structured Inference Networks for Nonlinear State Space Models
Rahul G. Krishnan
Uri Shalit
David Sontag
BDL
19
452
0
30 Sep 2016
Cooperative Training of Descriptor and Generator Networks
Cooperative Training of Descriptor and Generator Networks
Jianwen Xie
Yang Lu
Ruiqi Gao
Song-Chun Zhu
Ying Nian Wu
GAN
26
140
0
29 Sep 2016
Semantic Parsing with Semi-Supervised Sequential Autoencoders
Semantic Parsing with Semi-Supervised Sequential Autoencoders
Tomás Kociský
Gábor Melis
Edward Grefenstette
Chris Dyer
Wang Ling
Phil Blunsom
Karl Moritz Hermann
30
79
0
29 Sep 2016
Variational Autoencoder for Deep Learning of Images, Labels and Captions
Variational Autoencoder for Deep Learning of Images, Labels and Captions
Yunchen Pu
Zhe Gan
Ricardo Henao
Xin Yuan
Chunyuan Li
Andrew Stevens
Lawrence Carin
BDL
CoGe
33
746
0
28 Sep 2016
Character Sequence Models for ColorfulWords
Character Sequence Models for ColorfulWords
Kazuya Kawakami
Chris Dyer
Bryan R. Routledge
Noah A. Smith
3DV
25
17
0
28 Sep 2016
Neural Photo Editing with Introspective Adversarial Networks
Neural Photo Editing with Introspective Adversarial Networks
Andrew Brock
Theodore Lim
J. Ritchie
Nick Weston
GAN
27
457
0
22 Sep 2016
Enabling Dark Energy Science with Deep Generative Models of Galaxy
  Images
Enabling Dark Energy Science with Deep Generative Models of Galaxy Images
Siamak Ravanbakhsh
F. Lanusse
Rachel Mandelbaum
J. Schneider
Barnabás Póczós
30
65
0
19 Sep 2016
Label-Free Supervision of Neural Networks with Physics and Domain
  Knowledge
Label-Free Supervision of Neural Networks with Physics and Domain Knowledge
Russell Stewart
Stefano Ermon
23
344
0
18 Sep 2016
Towards Deep Symbolic Reinforcement Learning
Towards Deep Symbolic Reinforcement Learning
M. Garnelo
Kai Arulkumaran
Murray Shanahan
30
225
0
18 Sep 2016
SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient
SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient
Lantao Yu
Weinan Zhang
Jun Wang
Yong Yu
GAN
20
2,387
0
18 Sep 2016
Select-Additive Learning: Improving Generalization in Multimodal
  Sentiment Analysis
Select-Additive Learning: Improving Generalization in Multimodal Sentiment Analysis
Haohan Wang
Aaksha Meghawat
Louis-Philippe Morency
Eric Xing
21
151
0
16 Sep 2016
Hierarchical Multiscale Recurrent Neural Networks
Hierarchical Multiscale Recurrent Neural Networks
Junyoung Chung
Sungjin Ahn
Yoshua Bengio
BDL
40
534
0
06 Sep 2016
What makes ImageNet good for transfer learning?
What makes ImageNet good for transfer learning?
Minyoung Huh
Pulkit Agrawal
Alexei A. Efros
OOD
SSeg
VLM
SSL
62
671
0
30 Aug 2016
Visualizing and Understanding Sum-Product Networks
Visualizing and Understanding Sum-Product Networks
Antonio Vergari
Nicola Di Mauro
F. Esposito
FAtt
AAML
TPM
24
45
0
29 Aug 2016
Learning Temporal Transformations From Time-Lapse Videos
Learning Temporal Transformations From Time-Lapse Videos
Yipin Zhou
Tamara L. Berg
30
148
0
27 Aug 2016
LFADS - Latent Factor Analysis via Dynamical Systems
LFADS - Latent Factor Analysis via Dynamical Systems
David Sussillo
Rafal Jozefowicz
L. F. Abbott
C. Pandarinath
AI4CE
29
89
0
22 Aug 2016
BBQ-Networks: Efficient Exploration in Deep Reinforcement Learning for
  Task-Oriented Dialogue Systems
BBQ-Networks: Efficient Exploration in Deep Reinforcement Learning for Task-Oriented Dialogue Systems
Zachary Chase Lipton
Xiujun Li
Jianfeng Gao
Lihong Li
Faisal Ahmed
Li Deng
24
6
0
17 Aug 2016
Regularization for Unsupervised Deep Neural Nets
Regularization for Unsupervised Deep Neural Nets
Baiyang Wang
Diego Klabjan
BDL
23
25
0
15 Aug 2016
Generative and Discriminative Voxel Modeling with Convolutional Neural
  Networks
Generative and Discriminative Voxel Modeling with Convolutional Neural Networks
Andrew Brock
Theodore Lim
J. Ritchie
Nick Weston
26
577
0
15 Aug 2016
Deep Survival Analysis
Deep Survival Analysis
Rajesh Ranganath
A. Perotte
Noémie Elhadad
David M. Blei
22
197
0
06 Aug 2016
Learning a Driving Simulator
Learning a Driving Simulator
Eder Santana
George Hotz
GAN
28
226
0
03 Aug 2016
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