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Avoiding Latent Variable Collapse With Generative Skip Models
v1v2 (latest)

Avoiding Latent Variable Collapse With Generative Skip Models

12 July 2018
Adji Bousso Dieng
Yoon Kim
Alexander M. Rush
David M. Blei
    DRL
ArXiv (abs)PDFHTML

Papers citing "Avoiding Latent Variable Collapse With Generative Skip Models"

47 / 97 papers shown
Autoencoder Image Interpolation by Shaping the Latent Space
Autoencoder Image Interpolation by Shaping the Latent Space
Alon Oring
Z. Yakhini
Y. Hel-Or
162
2
0
04 Aug 2020
Pairwise Supervised Hashing with Bernoulli Variational Auto-Encoder and
  Self-Control Gradient Estimator
Pairwise Supervised Hashing with Bernoulli Variational Auto-Encoder and Self-Control Gradient Estimator
Siamak Zamani Dadaneh
Shahin Boluki
Mingzhang Yin
Mingyuan Zhou
Xiaoning Qian
BDLDRL
108
24
0
21 May 2020
Preventing Posterior Collapse with Levenshtein Variational Autoencoder
Preventing Posterior Collapse with Levenshtein Variational Autoencoder
Serhii Havrylov
Ivan Titov
DRL
193
20
0
30 Apr 2020
A Batch Normalized Inference Network Keeps the KL Vanishing Away
A Batch Normalized Inference Network Keeps the KL Vanishing AwayAnnual Meeting of the Association for Computational Linguistics (ACL), 2020
Qile Zhu
Jianlin Su
Wei Bi
Xiaojiang Liu
Xiyao Ma
Xiaolin Li
D. Wu
BDLDRL
161
64
0
27 Apr 2020
Improve Variational Autoencoder for Text Generationwith Discrete Latent
  Bottleneck
Improve Variational Autoencoder for Text Generationwith Discrete Latent Bottleneck
Yang Zhao
Ping Yu
Suchismit Mahapatra
Qinliang Su
Changyou Chen
DRL
213
2
0
22 Apr 2020
On the Encoder-Decoder Incompatibility in Variational Text Modeling and
  Beyond
On the Encoder-Decoder Incompatibility in Variational Text Modeling and BeyondAnnual Meeting of the Association for Computational Linguistics (ACL), 2020
Chen Henry Wu
P. Wang
Wenjie Wang
DRL
120
4
0
20 Apr 2020
Optimus: Organizing Sentences via Pre-trained Modeling of a Latent Space
Optimus: Organizing Sentences via Pre-trained Modeling of a Latent SpaceConference on Empirical Methods in Natural Language Processing (EMNLP), 2020
Chunyuan Li
Xiang Gao
Yuan Li
Baolin Peng
Xiujun Li
Yizhe Zhang
Jianfeng Gao
SSLDRL
476
194
0
05 Apr 2020
Characterizing and Avoiding Problematic Global Optima of Variational
  Autoencoders
Characterizing and Avoiding Problematic Global Optima of Variational AutoencodersSymposium on Advances in Approximate Bayesian Inference (AABI), 2020
Yaniv Yacoby
Weiwei Pan
Finale Doshi-Velez
DRL
148
4
0
17 Mar 2020
Curriculum By Smoothing
Curriculum By Smoothing
Samarth Sinha
Animesh Garg
Hugo Larochelle
369
7
0
03 Mar 2020
Paraphrase Generation with Latent Bag of Words
Paraphrase Generation with Latent Bag of WordsNeural Information Processing Systems (NeurIPS), 2020
Yao Fu
Yansong Feng
John P. Cunningham
BDL
265
102
0
07 Jan 2020
The Usual Suspects? Reassessing Blame for VAE Posterior Collapse
The Usual Suspects? Reassessing Blame for VAE Posterior CollapseInternational Conference on Machine Learning (ICML), 2019
Bin Dai
Ziyu Wang
David Wipf
DRL
171
85
0
23 Dec 2019
Learning Representations by Maximizing Mutual Information in Variational
  Autoencoders
Learning Representations by Maximizing Mutual Information in Variational AutoencodersInternational Symposium on Information Theory (ISIT), 2019
Ali Lotfi-Rezaabad
S. Vishwanath
DRLSSL
150
43
0
21 Dec 2019
SAG-VAE: End-to-end Joint Inference of Data Representations and Feature
  Relations
SAG-VAE: End-to-end Joint Inference of Data Representations and Feature RelationsIEEE International Joint Conference on Neural Network (IJCNN), 2019
Chen Wang
Chengyuan Deng
Vladimir A. Ivanov
GNNDRL
164
6
0
27 Nov 2019
A Stable Variational Autoencoder for Text Modelling
A Stable Variational Autoencoder for Text ModellingInternational Conference on Natural Language Generation (INLG), 2019
Ruizhe Li
Xiao Li
Chenghua Lin
Matthew Collinson
Rui Mao
DRLBDL
117
24
0
13 Nov 2019
On Posterior Collapse and Encoder Feature Dispersion in Sequence VAEs
On Posterior Collapse and Encoder Feature Dispersion in Sequence VAEs
Teng Long
Yanshuai Cao
Jackie C.K. Cheung
153
7
0
10 Nov 2019
Don't Blame the ELBO! A Linear VAE Perspective on Posterior Collapse
Don't Blame the ELBO! A Linear VAE Perspective on Posterior CollapseNeural Information Processing Systems (NeurIPS), 2019
James Lucas
George Tucker
Roger C. Grosse
Mohammad Norouzi
CoGeDRL
262
197
0
06 Nov 2019
An Information Theory Approach on Deciding Spectroscopic Follow Ups
An Information Theory Approach on Deciding Spectroscopic Follow UpsAstronomical Journal (AJ), 2019
Javiera Astudillo
P. Protopapas
K. Pichara
P. Huijse
112
4
0
06 Nov 2019
Enhancing VAEs for Collaborative Filtering: Flexible Priors & Gating
  Mechanisms
Enhancing VAEs for Collaborative Filtering: Flexible Priors & Gating MechanismsACM Conference on Recommender Systems (RecSys), 2019
Daeryong Kim
B. Suh
124
64
0
03 Nov 2019
Mitigating the Effects of Non-Identifiability on Inference for Bayesian
  Neural Networks with Latent Variables
Mitigating the Effects of Non-Identifiability on Inference for Bayesian Neural Networks with Latent VariablesJournal of machine learning research (JMLR), 2019
Yaniv Yacoby
Weiwei Pan
Finale Doshi-Velez
BDLUQCV
443
1
0
01 Nov 2019
Inverse Graphics: Unsupervised Learning of 3D Shapes from Single Images
Inverse Graphics: Unsupervised Learning of 3D Shapes from Single Images
Talip Uçar
114
1
0
31 Oct 2019
Bridging the ELBO and MMD
Bridging the ELBO and MMD
Talip Uçar
DRL
76
4
0
29 Oct 2019
Prescribed Generative Adversarial Networks
Prescribed Generative Adversarial Networks
Adji Bousso Dieng
Francisco J. R. Ruiz
David M. Blei
Michalis K. Titsias
GANDRL
218
62
0
09 Oct 2019
Re-balancing Variational Autoencoder Loss for Molecule Sequence
  Generation
Re-balancing Variational Autoencoder Loss for Molecule Sequence GenerationACM International Conference on Bioinformatics, Computational Biology and Biomedicine (ACM-BCB), 2019
Chao-chao Yan
Sheng Wang
Jinyu Yang
Qifeng Bai
Junzhou Huang
DRL
201
36
0
01 Oct 2019
On the Importance of the Kullback-Leibler Divergence Term in Variational
  Autoencoders for Text Generation
On the Importance of the Kullback-Leibler Divergence Term in Variational Autoencoders for Text GenerationConference on Empirical Methods in Natural Language Processing (EMNLP), 2019
Victor Prokhorov
Ehsan Shareghi
Yingzhen Li
Mohammad Taher Pilehvar
Nigel Collier
DRL
184
33
0
30 Sep 2019
Probabilistic Forecasting using Deep Generative Models
Probabilistic Forecasting using Deep Generative Models
A. Fanfarillo
B. Roozitalab
Weiming Hu
G. Cervone
86
19
0
26 Sep 2019
Improved Variational Neural Machine Translation by Promoting Mutual
  Information
Improved Variational Neural Machine Translation by Promoting Mutual Information
Arya D. McCarthy
Xian Li
Jiatao Gu
Ning Dong
DRL
116
8
0
19 Sep 2019
Mixture Content Selection for Diverse Sequence Generation
Mixture Content Selection for Diverse Sequence GenerationConference on Empirical Methods in Natural Language Processing (EMNLP), 2019
Jaemin Cho
Minjoon Seo
Hannaneh Hajishirzi
158
63
0
04 Sep 2019
A Surprisingly Effective Fix for Deep Latent Variable Modeling of Text
A Surprisingly Effective Fix for Deep Latent Variable Modeling of TextConference on Empirical Methods in Natural Language Processing (EMNLP), 2019
Bohan Li
Junxian He
Graham Neubig
Taylor Berg-Kirkpatrick
Yiming Yang
DRL
142
73
0
02 Sep 2019
Conditional Flow Variational Autoencoders for Structured Sequence
  Prediction
Conditional Flow Variational Autoencoders for Structured Sequence Prediction
Apratim Bhattacharyya
M. Hanselmann
Mario Fritz
Bernt Schiele
C. Straehle
BDLDRLAI4TS
231
93
0
24 Aug 2019
Latent-Variable Non-Autoregressive Neural Machine Translation with
  Deterministic Inference Using a Delta Posterior
Latent-Variable Non-Autoregressive Neural Machine Translation with Deterministic Inference Using a Delta PosteriorAAAI Conference on Artificial Intelligence (AAAI), 2019
Raphael Shu
Jason D. Lee
Hideki Nakayama
Dong Wang
BDL
427
122
0
20 Aug 2019
Improve variational autoEncoder with auxiliary softmax multiclassifier
Improve variational autoEncoder with auxiliary softmax multiclassifier
Yao Li
DRL
193
0
0
17 Aug 2019
Noise Contrastive Variational Autoencoders
O. Ganea
Yashas Annadani
Gary Bécigneul
DRL
121
0
0
23 Jul 2019
Autoencoding sensory substitution
Autoencoding sensory substitution
Viktor Tóth
L. Parkkonen
79
7
0
14 Jul 2019
Reweighted Expectation Maximization
Reweighted Expectation Maximization
Adji Bousso Dieng
John Paisley
VLMDRL
179
17
0
13 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
156
6
0
04 Jun 2019
Practical and Consistent Estimation of f-Divergences
Practical and Consistent Estimation of f-DivergencesNeural Information Processing Systems (NeurIPS), 2019
Paul Kishan Rubenstein
Olivier Bousquet
Josip Djolonga
C. Riquelme
Ilya O. Tolstikhin
209
48
0
27 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
188
4
0
17 May 2019
Effective Estimation of Deep Generative Language Models
Effective Estimation of Deep Generative Language Models
Tom Pelsmaeker
Wilker Aziz
BDL
252
28
0
17 Apr 2019
Meta-Learning surrogate models for sequential decision making
Meta-Learning surrogate models for sequential decision making
Alexandre Galashov
Jonathan Richard Schwarz
Hyunjik Kim
M. Garnelo
D. Saxton
Pushmeet Kohli
S. M. Ali Eslami
Yee Whye Teh
BDLOffRL
230
25
0
28 Mar 2019
Cyclical Annealing Schedule: A Simple Approach to Mitigating KL
  Vanishing
Cyclical Annealing Schedule: A Simple Approach to Mitigating KL Vanishing
Hao Fu
Chunyuan Li
Xiaodong Liu
Jianfeng Gao
Asli Celikyilmaz
Lawrence Carin
ODL
276
413
0
25 Mar 2019
STCN: Stochastic Temporal Convolutional Networks
STCN: Stochastic Temporal Convolutional Networks
Emre Aksan
Otmar Hilliges
BDL
180
67
0
18 Feb 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
338
222
0
06 Feb 2019
Uncertainty Quantification in Deep MRI Reconstruction
Uncertainty Quantification in Deep MRI ReconstructionIEEE Transactions on Medical Imaging (TMI), 2019
Vineet Edupuganti
Morteza Mardani
S. Vasanawala
John M. Pauly
UQCV
266
109
0
31 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
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
Sparsity in Variational Autoencoders
Sparsity in Variational Autoencoders
Andrea Asperti
BDLDRL
176
12
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
284
46
0
17 Dec 2018
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