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Variational Lossy Autoencoder
v1v2 (latest)

Variational Lossy Autoencoder

8 November 2016
Xi Chen
Diederik P. Kingma
Tim Salimans
Yan Duan
Prafulla Dhariwal
John Schulman
Ilya Sutskever
Pieter Abbeel
    DRLSSLGAN
ArXiv (abs)PDFHTML

Papers citing "Variational Lossy Autoencoder"

50 / 398 papers shown
Improve variational autoEncoder with auxiliary softmax multiclassifier
Improve variational autoEncoder with auxiliary softmax multiclassifier
Yao Li
DRL
190
0
0
17 Aug 2019
Video Compression With Rate-Distortion Autoencoders
Video Compression With Rate-Distortion AutoencodersIEEE International Conference on Computer Vision (ICCV), 2019
A. Habibian
T. V. Rozendaal
Jakub M. Tomczak
Taco S. Cohen
VGen
263
224
0
14 Aug 2019
Likelihood Contribution based Multi-scale Architecture for Generative
  Flows
Likelihood Contribution based Multi-scale Architecture for Generative Flows
Hari Prasanna Das
Pieter Abbeel
C. Spanos
DRLAI4CE
163
5
0
05 Aug 2019
Noise Contrastive Variational Autoencoders
O. Ganea
Yashas Annadani
Gary Bécigneul
DRL
117
0
0
23 Jul 2019
Neural Drum Machine : An Interactive System for Real-time Synthesis of
  Drum Sounds
Neural Drum Machine : An Interactive System for Real-time Synthesis of Drum SoundsInternational Conference on Innovative Computing and Cloud Computing (ICCC), 2019
Cyran Aouameur
P. Esling
Gaëtan Hadjeres
180
24
0
04 Jul 2019
Universal audio synthesizer control with normalizing flows
Universal audio synthesizer control with normalizing flows
P. Esling
Naotake Masuda
Adrien Bardet
R. Despres
Axel Chemla-Romeu-Santos
117
45
0
01 Jul 2019
PointFlow: 3D Point Cloud Generation with Continuous Normalizing Flows
PointFlow: 3D Point Cloud Generation with Continuous Normalizing FlowsIEEE International Conference on Computer Vision (ICCV), 2019
Guandao Yang
Xun Huang
Jinwei Gu
Ming-Yuan Liu
Serge J. Belongie
Bharath Hariharan
3DPC
525
758
0
28 Jun 2019
The Functional Neural Process
The Functional Neural ProcessNeural Information Processing Systems (NeurIPS), 2019
Christos Louizos
Xiahan Shi
Klamer Schutte
Max Welling
BDL
241
81
0
19 Jun 2019
Reweighted Expectation Maximization
Reweighted Expectation Maximization
Adji Bousso Dieng
John Paisley
VLMDRL
177
17
0
13 Jun 2019
An Introduction to Variational Autoencoders
An Introduction to Variational Autoencoders
Diederik P. Kingma
Max Welling
BDLSSLDRL
742
2,796
0
06 Jun 2019
A Cross-Sentence Latent Variable Model for Semi-Supervised Text Sequence
  Matching
A Cross-Sentence Latent Variable Model for Semi-Supervised Text Sequence MatchingAnnual Meeting of the Association for Computational Linguistics (ACL), 2019
Jihun Choi
Taeuk Kim
Sang-goo Lee
BDL
153
6
0
04 Jun 2019
Generating Diverse High-Fidelity Images with VQ-VAE-2
Generating Diverse High-Fidelity Images with VQ-VAE-2Neural Information Processing Systems (NeurIPS), 2019
Ali Razavi
Aaron van den Oord
Oriol Vinyals
DRLBDL
601
2,152
0
02 Jun 2019
On the Necessity and Effectiveness of Learning the Prior of Variational
  Auto-Encoder
On the Necessity and Effectiveness of Learning the Prior of Variational Auto-Encoder
Haowen Xu
Wenxiao Chen
Jinlin Lai
Zhihan Li
Youjian Zhao
Dan Pei
DRLBDL
166
17
0
31 May 2019
Educating Text Autoencoders: Latent Representation Guidance via
  Denoising
Educating Text Autoencoders: Latent Representation Guidance via Denoising
T. Shen
Jonas W. Mueller
Regina Barzilay
Tommi Jaakkola
195
4
0
29 May 2019
Unified Probabilistic Deep Continual Learning through Generative Replay
  and Open Set Recognition
Unified Probabilistic Deep Continual Learning through Generative Replay and Open Set RecognitionJournal of Imaging (J. Imaging), 2019
Martin Mundt
Iuliia Pliushch
Sagnik Majumder
Yongwon Hong
Visvanathan Ramesh
UQCVBDL
261
43
0
28 May 2019
The Variational InfoMax AutoEncoder
The Variational InfoMax AutoEncoderIEEE International Joint Conference on Neural Network (IJCNN), 2019
Vincenzo Crescimanna
Bruce P. Graham
DRL
161
3
0
25 May 2019
mu-Forcing: Training Variational Recurrent Autoencoders for Text
  Generation
mu-Forcing: Training Variational Recurrent Autoencoders for Text Generation
Dayiheng Liu
Xu Yang
Feng He
Yuanyuan Chen
Jiancheng Lv
DRLBDL
128
41
0
24 May 2019
Compression with Flows via Local Bits-Back Coding
Compression with Flows via Local Bits-Back CodingNeural Information Processing Systems (NeurIPS), 2019
Jonathan Ho
Evan Lohn
Pieter Abbeel
251
61
0
21 May 2019
Dueling Decoders: Regularizing Variational Autoencoder Latent Spaces
Dueling Decoders: Regularizing Variational Autoencoder Latent Spaces
Bryan Seybold
Emily Fertig
Alexander A. Alemi
Ian S. Fischer
DRL
183
4
0
17 May 2019
Bit-Swap: Recursive Bits-Back Coding for Lossless Compression with
  Hierarchical Latent Variables
Bit-Swap: Recursive Bits-Back Coding for Lossless Compression with Hierarchical Latent VariablesInternational Conference on Machine Learning (ICML), 2019
F. Kingma
Pieter Abbeel
Jonathan Ho
344
106
0
16 May 2019
MoGlow: Probabilistic and controllable motion synthesis using
  normalising flows
MoGlow: Probabilistic and controllable motion synthesis using normalising flowsACM Transactions on Graphics (TOG), 2019
G. Henter
Simon Alexanderson
Jonas Beskow
319
103
0
16 May 2019
Learning Hierarchical Priors in VAEs
Learning Hierarchical Priors in VAEsNeural Information Processing Systems (NeurIPS), 2019
Alexej Klushyn
Nutan Chen
Richard Kurle
Botond Cseke
Patrick van der Smagt
BDLCMLDRL
377
106
0
13 May 2019
Importance Weighted Hierarchical Variational Inference
Importance Weighted Hierarchical Variational InferenceNeural Information Processing Systems (NeurIPS), 2019
Artem Sobolev
Dmitry Vetrov
BDL
159
32
0
08 May 2019
Deep Residual Autoencoders for Expectation Maximization-inspired
  Dictionary Learning
Deep Residual Autoencoders for Expectation Maximization-inspired Dictionary Learning
Bahareh Tolooshams
Sourav Dey
Demba E. Ba
211
4
0
18 Apr 2019
Effective Estimation of Deep Generative Language Models
Effective Estimation of Deep Generative Language Models
Tom Pelsmaeker
Wilker Aziz
BDL
249
28
0
17 Apr 2019
Exact Rate-Distortion in Autoencoders via Echo Noise
Exact Rate-Distortion in Autoencoders via Echo Noise
Rob Brekelmans
Daniel Moyer
Aram Galstyan
Greg Ver Steeg
182
17
0
15 Apr 2019
Information Bottleneck and its Applications in Deep Learning
Information Bottleneck and its Applications in Deep Learning
Hassan Hafez-Kolahi
S. Kasaei
138
21
0
07 Apr 2019
From Variational to Deterministic Autoencoders
From Variational to Deterministic Autoencoders
Partha Ghosh
Mehdi S. M. Sajjadi
Antonio Vergari
Michael J. Black
Bernhard Schölkopf
DRL
467
292
0
29 Mar 2019
Adversarial Approximate Inference for Speech to Electroglottograph
  Conversion
Adversarial Approximate Inference for Speech to Electroglottograph Conversion
Prathosh A. P.
Varun Srivastava
Mayank Mishra
105
7
0
28 Mar 2019
Diagnosing and Enhancing VAE Models
Diagnosing and Enhancing VAE Models
Bin Dai
David Wipf
DRL
313
415
0
14 Mar 2019
Generative Graph Convolutional Network for Growing Graphs
Generative Graph Convolutional Network for Growing Graphs
Da Xu
Chuanwei Ruan
Kamiya Motwani
Evren Körpeoglu
Sushant Kumar
Kannan Achan
GNN
102
14
0
06 Mar 2019
Hierarchical Autoregressive Image Models with Auxiliary Decoders
Hierarchical Autoregressive Image Models with Auxiliary Decoders
J. Fauw
Sander Dieleman
Karen Simonyan
GAN
252
39
0
06 Mar 2019
Learning Dynamics Model in Reinforcement Learning by Incorporating the
  Long Term Future
Learning Dynamics Model in Reinforcement Learning by Incorporating the Long Term Future
Nan Rosemary Ke
Amanpreet Singh
Ahmed Touati
Anirudh Goyal
Yoshua Bengio
Devi Parikh
Dhruv Batra
156
53
0
05 Mar 2019
adVAE: A self-adversarial variational autoencoder with Gaussian anomaly
  prior knowledge for anomaly detection
adVAE: A self-adversarial variational autoencoder with Gaussian anomaly prior knowledge for anomaly detectionKnowledge-Based Systems (KBS), 2019
Xuhong Wang
Ying Du
Shijie Lin
Ping Cui
Yuntian Shen
Yupu Yang
DRLViTUQCV
398
119
0
03 Mar 2019
BIVA: A Very Deep Hierarchy of Latent Variables for Generative Modeling
BIVA: A Very Deep Hierarchy of Latent Variables for Generative Modeling
Lars Maaløe
Marco Fraccaro
Valentin Liévin
Ole Winther
BDLDRL
335
222
0
06 Feb 2019
Towards Generating Long and Coherent Text with Multi-Level Latent
  Variable Models
Towards Generating Long and Coherent Text with Multi-Level Latent Variable ModelsAnnual Meeting of the Association for Computational Linguistics (ACL), 2019
Dinghan Shen
Asli Celikyilmaz
Yizhe Zhang
Liqun Chen
Xin Eric Wang
Jianfeng Gao
Lawrence Carin
DRL
231
55
0
01 Feb 2019
Latent Normalizing Flows for Discrete Sequences
Latent Normalizing Flows for Discrete SequencesInternational Conference on Machine Learning (ICML), 2019
Zachary M. Ziegler
Alexander M. Rush
BDLDRL
487
131
0
29 Jan 2019
Semi-Unsupervised Learning: Clustering and Classifying using
  Ultra-Sparse Labels
Semi-Unsupervised Learning: Clustering and Classifying using Ultra-Sparse Labels
M. Willetts
Stephen J. Roberts
Christopher C Holmes
201
5
0
24 Jan 2019
Lagging Inference Networks and Posterior Collapse in Variational
  Autoencoders
Lagging Inference Networks and Posterior Collapse in Variational Autoencoders
Junxian He
Daniel M. Spokoyny
Graham Neubig
Taylor Berg-Kirkpatrick
BDLDRL
275
287
0
16 Jan 2019
Variation Network: Learning High-level Attributes for Controlled Input
  Manipulation
Variation Network: Learning High-level Attributes for Controlled Input Manipulation
Gaëtan Hadjeres
Frank Nielsen
170
2
0
11 Jan 2019
Undirected Graphical Models as Approximate Posteriors
Undirected Graphical Models as Approximate Posteriors
Arash Vahdat
Evgeny Andriyash
W. Macready
219
2
0
11 Jan 2019
Preventing Posterior Collapse with delta-VAEs
Preventing Posterior Collapse with delta-VAEs
Ali Razavi
Aaron van den Oord
Ben Poole
Oriol Vinyals
DRL
309
180
0
10 Jan 2019
MAE: Mutual Posterior-Divergence Regularization for Variational
  AutoEncoders
MAE: Mutual Posterior-Divergence Regularization for Variational AutoEncoders
Xuezhe Ma
Chunting Zhou
Eduard H. Hovy
DRL
175
40
0
06 Jan 2019
Adaptive Density Estimation for Generative Models
Adaptive Density Estimation for Generative Models
Thomas Lucas
K. Shmelkov
Alahari Karteek
Cordelia Schmid
Jakob Verbeek
GANDRL
358
33
0
04 Jan 2019
Uncertainty Autoencoders: Learning Compressed Representations via
  Variational Information Maximization
Uncertainty Autoencoders: Learning Compressed Representations via Variational Information Maximization
Aditya Grover
Stefano Ermon
266
54
0
26 Dec 2018
A Factorial Mixture Prior for Compositional Deep Generative Models
A Factorial Mixture Prior for Compositional Deep Generative Models
Ulrich Paquet
Sumedh Ghaisas
O. Tieleman
CoGe
148
1
0
18 Dec 2018
A Tutorial on Deep Latent Variable Models of Natural Language
A Tutorial on Deep Latent Variable Models of Natural Language
Yoon Kim
Sam Wiseman
Alexander M. Rush
BDLVLM
282
46
0
17 Dec 2018
Recent Advances in Autoencoder-Based Representation Learning
Recent Advances in Autoencoder-Based Representation Learning
Michael Tschannen
Olivier Bachem
Mario Lucic
OODSSLDRL
214
483
0
12 Dec 2018
Learning Controllable Fair Representations
Learning Controllable Fair Representations
Jiaming Song
Pratyusha Kalluri
Aditya Grover
Shengjia Zhao
Stefano Ermon
FaML
262
183
0
11 Dec 2018
Disentangling Disentanglement in Variational Autoencoders
Disentangling Disentanglement in Variational Autoencoders
Emile Mathieu
Tom Rainforth
Siddharth Narayanaswamy
Yee Whye Teh
DRLCoGe
206
10
0
06 Dec 2018
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