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Variational Inference with Normalizing Flows
v1v2v3v4v5v6 (latest)

Variational Inference with Normalizing Flows

21 May 2015
Danilo Jimenez Rezende
S. Mohamed
    DRLBDL
ArXiv (abs)PDFHTML

Papers citing "Variational Inference with Normalizing Flows"

50 / 2,268 papers shown
Title
Latent Normalizing Flows for Discrete Sequences
Latent Normalizing Flows for Discrete Sequences
Zachary M. Ziegler
Alexander M. Rush
BDLDRL
119
129
0
29 Jan 2019
Discretizing Continuous Action Space for On-Policy Optimization
Discretizing Continuous Action Space for On-Policy Optimization
Yunhao Tang
Shipra Agrawal
OffRL
107
124
0
29 Jan 2019
We Are Not Your Real Parents: Telling Causal from Confounded using MDL
We Are Not Your Real Parents: Telling Causal from Confounded using MDL
David Kaltenpoth
Jilles Vreeken
CML
114
22
0
21 Jan 2019
Physics-Constrained Deep Learning for High-dimensional Surrogate
  Modeling and Uncertainty Quantification without Labeled Data
Physics-Constrained Deep Learning for High-dimensional Surrogate Modeling and Uncertainty Quantification without Labeled Data
Yinhao Zhu
N. Zabaras
P. Koutsourelakis
P. Perdikaris
PINNAI4CE
145
876
0
18 Jan 2019
Conditional deep surrogate models for stochastic, high-dimensional, and
  multi-fidelity systems
Conditional deep surrogate models for stochastic, high-dimensional, and multi-fidelity systems
Yibo Yang
P. Perdikaris
SyDaBDLAI4CE
66
56
0
15 Jan 2019
Posterior inference unchained with EL_2O
Posterior inference unchained with EL_2O
U. Seljak
Byeonghee Yu
79
10
0
14 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
94
171
0
10 Jan 2019
Dirichlet Variational Autoencoder
Dirichlet Variational Autoencoder
Weonyoung Joo
Wonsung Lee
Sungrae Park
Il-Chul Moon
BDLDRL
128
105
0
09 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
75
39
0
06 Jan 2019
Poincaré Wasserstein Autoencoder
Poincaré Wasserstein Autoencoder
Ivan Ovinnikov
97
17
0
05 Jan 2019
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
121
42
0
17 Dec 2018
AdaFlow: Domain-Adaptive Density Estimator with Application to Anomaly
  Detection and Unpaired Cross-Domain Translation
AdaFlow: Domain-Adaptive Density Estimator with Application to Anomaly Detection and Unpaired Cross-Domain Translation
Masataka Yamaguchi
Yuma Koizumi
Noboru Harada
91
37
0
14 Dec 2018
Encoding prior knowledge in the structure of the likelihood
Encoding prior knowledge in the structure of the likelihood
Jakob Knollmüller
T. Ensslin
69
11
0
11 Dec 2018
Learning Controllable Fair Representations
Learning Controllable Fair Representations
Jiaming Song
Pratyusha Kalluri
Aditya Grover
Shengjia Zhao
Stefano Ermon
FaML
98
180
0
11 Dec 2018
Bayesian Layers: A Module for Neural Network Uncertainty
Bayesian Layers: A Module for Neural Network Uncertainty
Dustin Tran
Michael W. Dusenberry
Mark van der Wilk
Danijar Hafner
UQCVBDL
131
124
0
10 Dec 2018
Partitioned Variational Inference: A unified framework encompassing
  federated and continual learning
Partitioned Variational Inference: A unified framework encompassing federated and continual learning
T. Bui
Cuong V Nguyen
S. Swaroop
Richard Turner
FedML
91
56
0
27 Nov 2018
Learning Attractor Dynamics for Generative Memory
Learning Attractor Dynamics for Generative Memory
Yan Wu
Greg Wayne
Karol Gregor
Timothy Lillicrap
BDL
98
18
0
23 Nov 2018
Spread Divergence
Spread Divergence
Mingtian Zhang
Peter Hayes
Thomas Bird
Raza Habib
David Barber
MedImUD
96
20
0
21 Nov 2018
Learning deep kernels for exponential family densities
Learning deep kernels for exponential family densities
W. Li
Danica J. Sutherland
Heiko Strathmann
Arthur Gretton
BDL
103
74
0
20 Nov 2018
The Theory and Algorithm of Ergodic Inference
The Theory and Algorithm of Ergodic Inference
Yichuan Zhang
33
2
0
17 Nov 2018
Sorting out Lipschitz function approximation
Sorting out Lipschitz function approximation
Cem Anil
James Lucas
Roger C. Grosse
98
325
0
13 Nov 2018
Adversarial Uncertainty Quantification in Physics-Informed Neural
  Networks
Adversarial Uncertainty Quantification in Physics-Informed Neural Networks
Yibo Yang
P. Perdikaris
AI4CEPINN
159
361
0
09 Nov 2018
Wasserstein variational gradient descent: From semi-discrete optimal
  transport to ensemble variational inference
Wasserstein variational gradient descent: From semi-discrete optimal transport to ensemble variational inference
L. Ambrogioni
Rémi Flamary
R. Tavenard
OT
63
13
0
07 Nov 2018
FloWaveNet : A Generative Flow for Raw Audio
FloWaveNet : A Generative Flow for Raw Audio
Sungwon Kim
Sang-gil Lee
Jongyoon Song
Jaehyeon Kim
Sungroh Yoon
116
169
0
06 Nov 2018
Invertible Residual Networks
Invertible Residual Networks
Jens Behrmann
Will Grathwohl
Ricky T. Q. Chen
David Duvenaud
J. Jacobsen
UQCVTPM
183
625
0
02 Nov 2018
WaveGlow: A Flow-based Generative Network for Speech Synthesis
WaveGlow: A Flow-based Generative Network for Speech Synthesis
R. Prenger
Rafael Valle
Bryan Catanzaro
168
1,036
0
31 Oct 2018
Hybrid Generative-Discriminative Models for Inverse Materials Design
Hybrid Generative-Discriminative Models for Inverse Materials Design
Phuoc Nguyen
T. Tran
Sunil R. Gupta
Santu Rana
Svetha Venkatesh
AI4CEPINN
39
6
0
31 Oct 2018
Towards Principled Uncertainty Estimation for Deep Neural Networks
Towards Principled Uncertainty Estimation for Deep Neural Networks
Richard E. Harang
Ethan M. Rudd
BDLUQCV
83
6
0
29 Oct 2018
Gaussian Process Prior Variational Autoencoders
Gaussian Process Prior Variational Autoencoders
F. P. Casale
Adrian Dalca
Luca Saglietti
Jennifer Listgarten
Nicolò Fusi
BDLCML
75
139
0
28 Oct 2018
Resampled Priors for Variational Autoencoders
Resampled Priors for Variational Autoencoders
Matthias Bauer
A. Mnih
BDLDRL
122
111
0
26 Oct 2018
Good Initializations of Variational Bayes for Deep Models
Good Initializations of Variational Bayes for Deep Models
Simone Rossi
Pietro Michiardi
Maurizio Filippone
BDL
130
22
0
18 Oct 2018
Metropolis-Hastings view on variational inference and adversarial
  training
Metropolis-Hastings view on variational inference and adversarial training
Kirill Neklyudov
Evgenii Egorov
Pavel Shvechikov
Dmitry Vetrov
GAN
83
13
0
16 Oct 2018
The Deep Weight Prior
The Deep Weight Prior
Andrei Atanov
Arsenii Ashukha
Kirill Struminsky
Dmitry Vetrov
Max Welling
BDL
125
37
0
16 Oct 2018
Doubly Reparameterized Gradient Estimators for Monte Carlo Objectives
Doubly Reparameterized Gradient Estimators for Monte Carlo Objectives
George Tucker
Dieterich Lawson
S. Gu
Chris J. Maddison
BDL
91
110
0
09 Oct 2018
Deep Diffeomorphic Normalizing Flows
Deep Diffeomorphic Normalizing Flows
Hadi Salman
Payman Yadollahpour
Tom Fletcher
N. Batmanghelich
78
27
0
08 Oct 2018
Deep Generative Video Compression
Deep Generative Video Compression
Jun Han
Salvator Lombardo
Christopher Schroers
Stephan Mandt
VGen
87
58
0
05 Oct 2018
WAIC, but Why? Generative Ensembles for Robust Anomaly Detection
WAIC, but Why? Generative Ensembles for Robust Anomaly Detection
Hyun-Jae Choi
Eric Jang
Alexander A. Alemi
OODD
114
82
0
02 Oct 2018
FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative
  Models
FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative Models
Will Grathwohl
Ricky T. Q. Chen
J. Bettencourt
Ilya Sutskever
David Duvenaud
DRL
169
883
0
02 Oct 2018
Taming VAEs
Taming VAEs
Danilo Jimenez Rezende
Fabio Viola
DRLCML
72
186
0
01 Oct 2018
Generative replay with feedback connections as a general strategy for
  continual learning
Generative replay with feedback connections as a general strategy for continual learning
Gido M. van de Ven
A. Tolias
CLLKELM
107
226
0
27 Sep 2018
Boosting Trust Region Policy Optimization by Normalizing Flows Policy
Boosting Trust Region Policy Optimization by Normalizing Flows Policy
Yunhao Tang
Shipra Agrawal
TPM
110
31
0
27 Sep 2018
Monge-Ampère Flow for Generative Modeling
Monge-Ampère Flow for Generative Modeling
Linfeng Zhang
E. Weinan
Lei Wang
DRL
97
63
0
26 Sep 2018
InfoSSM: Interpretable Unsupervised Learning of Nonparametric
  State-Space Model for Multi-modal Dynamics
InfoSSM: Interpretable Unsupervised Learning of Nonparametric State-Space Model for Multi-modal Dynamics
Young-Jin Park
Han-Lim Choi
23
0
0
19 Sep 2018
Predictive Collective Variable Discovery with Deep Bayesian Models
Predictive Collective Variable Discovery with Deep Bayesian Models
M. Schöberl
N. Zabaras
P. Koutsourelakis
66
34
0
18 Sep 2018
Variational Autoencoder with Implicit Optimal Priors
Variational Autoencoder with Implicit Optimal Priors
Hiroshi Takahashi
Tomoharu Iwata
Yuki Yamanaka
Masanori Yamada
Satoshi Yagi
DRL
107
65
0
14 Sep 2018
Discriminator-Actor-Critic: Addressing Sample Inefficiency and Reward
  Bias in Adversarial Imitation Learning
Discriminator-Actor-Critic: Addressing Sample Inefficiency and Reward Bias in Adversarial Imitation Learning
Ilya Kostrikov
Kumar Krishna Agrawal
Debidatta Dwibedi
Sergey Levine
Jonathan Tompson
111
259
0
09 Sep 2018
Exploiting Invertible Decoders for Unsupervised Sentence Representation
  Learning
Exploiting Invertible Decoders for Unsupervised Sentence Representation Learning
Shuai Tang
V. D. Sa
SSL
51
1
0
08 Sep 2018
Improving Explorability in Variational Inference with Annealed
  Variational Objectives
Improving Explorability in Variational Inference with Annealed Variational Objectives
Chin-Wei Huang
Shawn Tan
Alexandre Lacoste
Aaron Courville
DRL
52
48
0
06 Sep 2018
Stochastic Particle-Optimization Sampling and the Non-Asymptotic
  Convergence Theory
Stochastic Particle-Optimization Sampling and the Non-Asymptotic Convergence Theory
Jianyi Zhang
Ruiyi Zhang
Lawrence Carin
Changyou Chen
146
46
0
05 Sep 2018
Unsupervised Learning of Syntactic Structure with Invertible Neural
  Projections
Unsupervised Learning of Syntactic Structure with Invertible Neural Projections
Junxian He
Graham Neubig
Taylor Berg-Kirkpatrick
BDL
57
41
0
28 Aug 2018
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