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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
Learning Bijective Feature Maps for Linear ICA
Learning Bijective Feature Maps for Linear ICA
A. Camuto
M. Willetts
Brooks Paige
Chris Holmes
Stephen J. Roberts
46
3
0
18 Feb 2020
Gravitational-wave parameter estimation with autoregressive neural
  network flows
Gravitational-wave parameter estimation with autoregressive neural network flows
Stephen R. Green
C. Simpson
J. Gair
BDL
130
86
0
18 Feb 2020
Deep Gaussian Markov Random Fields
Deep Gaussian Markov Random Fields
Per Sidén
Fredrik Lindsten
BDL
59
22
0
18 Feb 2020
Augmented Normalizing Flows: Bridging the Gap Between Generative Flows
  and Latent Variable Models
Augmented Normalizing Flows: Bridging the Gap Between Generative Flows and Latent Variable Models
Chin-Wei Huang
Laurent Dinh
Aaron Courville
DRL
115
89
0
17 Feb 2020
Learning Robust Representations via Multi-View Information Bottleneck
Learning Robust Representations via Multi-View Information Bottleneck
Marco Federici
Anjan Dutta
Patrick Forré
Nate Kushman
Zeynep Akata
SLR
83
260
0
17 Feb 2020
Stochastic Normalizing Flows
Stochastic Normalizing Flows
Hao Wu
Jonas Köhler
Frank Noé
156
186
0
16 Feb 2020
The Phantom Steering Effect in Q&A Websites
The Phantom Steering Effect in Q&A Websites
Nicholas Hoernle
Gregory Kehne
Ariel D. Procaccia
Y. Gal
LLMSV
13
2
0
14 Feb 2020
PACOH: Bayes-Optimal Meta-Learning with PAC-Guarantees
PACOH: Bayes-Optimal Meta-Learning with PAC-Guarantees
Jonas Rothfuss
Vincent Fortuin
Martin Josifoski
Andreas Krause
UQCV
93
127
0
13 Feb 2020
Black-Box Optimization with Local Generative Surrogates
Black-Box Optimization with Local Generative Surrogates
S. Shirobokov
V. Belavin
Michael Kagan
Andrey Ustyuzhanin
A. G. Baydin
44
3
0
11 Feb 2020
Learning Stochastic Behaviour from Aggregate Data
Learning Stochastic Behaviour from Aggregate Data
Shaojun Ma
Shu Liu
H. Zha
Haomin Zhou
144
15
0
10 Feb 2020
TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular
  Dynamics
TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular Dynamics
Alexander Tong
Jessie Huang
Guy Wolf
David van Dijk
Smita Krishnaswamy
77
177
0
09 Feb 2020
Learning Implicit Generative Models with Theoretical Guarantees
Learning Implicit Generative Models with Theoretical Guarantees
Yuan Gao
Jian Huang
Yuling Jiao
Jin Liu
66
7
0
07 Feb 2020
The k-tied Normal Distribution: A Compact Parameterization of Gaussian
  Mean Field Posteriors in Bayesian Neural Networks
The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks
J. Swiatkowski
Kevin Roth
Bastiaan S. Veeling
Linh-Tam Tran
Joshua V. Dillon
Jasper Snoek
Stephan Mandt
Tim Salimans
Rodolphe Jenatton
Sebastian Nowozin
BDL
89
47
0
07 Feb 2020
Closing the Dequantization Gap: PixelCNN as a Single-Layer Flow
Closing the Dequantization Gap: PixelCNN as a Single-Layer Flow
Didrik Nielsen
Ole Winther
MQ
235
13
0
06 Feb 2020
Normalizing Flows on Tori and Spheres
Normalizing Flows on Tori and Spheres
Danilo Jimenez Rezende
George Papamakarios
S. Racanière
M. S. Albergo
G. Kanwar
P. Shanahan
Kyle Cranmer
TPM
93
157
0
06 Feb 2020
Learning Extremal Representations with Deep Archetypal Analysis
Learning Extremal Representations with Deep Archetypal Analysis
S. Keller
M. Samarin
Fabricio Arend Torres
Mario Wieser
Volker Roth
78
24
0
03 Feb 2020
Automatic structured variational inference
Automatic structured variational inference
L. Ambrogioni
Kate Lin
Emily Fertig
Sharad Vikram
Max Hinne
Dave Moore
Marcel van Gerven
BDL
84
31
0
03 Feb 2020
Variational Item Response Theory: Fast, Accurate, and Expressive
Variational Item Response Theory: Fast, Accurate, and Expressive
Mike Wu
R. Davis
B. Domingue
Chris Piech
Noah D. Goodman
OffRL
107
55
0
01 Feb 2020
GraphAF: a Flow-based Autoregressive Model for Molecular Graph
  Generation
GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generation
Chence Shi
Minkai Xu
Zhaocheng Zhu
Weinan Zhang
Ming Zhang
Jian Tang
237
439
0
26 Jan 2020
Safe Robot Navigation via Multi-Modal Anomaly Detection
Safe Robot Navigation via Multi-Modal Anomaly Detection
Lorenz Wellhausen
René Ranftl
Marco Hutter
89
77
0
22 Jan 2020
A Deep Learning Algorithm for High-Dimensional Exploratory Item Factor
  Analysis
A Deep Learning Algorithm for High-Dimensional Exploratory Item Factor Analysis
Christopher J. Urban
Daniel J. Bauer
BDL
81
33
0
22 Jan 2020
i-flow: High-dimensional Integration and Sampling with Normalizing Flows
i-flow: High-dimensional Integration and Sampling with Normalizing Flows
Christina Gao
J. Isaacson
Claudius Krause
AI4CE
83
111
0
15 Jan 2020
Invertible Generative Modeling using Linear Rational Splines
Invertible Generative Modeling using Linear Rational Splines
H. M. Dolatabadi
S. Erfani
C. Leckie
127
65
0
15 Jan 2020
Anomaly Detection with Density Estimation
Anomaly Detection with Density Estimation
Benjamin Nachman
David Shih
74
220
0
14 Jan 2020
Information Newton's flow: second-order optimization method in
  probability space
Information Newton's flow: second-order optimization method in probability space
Yifei Wang
Wuchen Li
111
31
0
13 Jan 2020
Learning Generative Models using Denoising Density Estimators
Learning Generative Models using Denoising Density Estimators
Siavash Bigdeli
Geng Lin
Tiziano Portenier
L. A. Dunbar
Matthias Zwicker
DiffM
106
16
0
08 Jan 2020
A Probability Density Theory for Spin-Glass Systems
A Probability Density Theory for Spin-Glass Systems
Gavin Hartnett
Masoud Mohseni
68
3
0
03 Jan 2020
Discrete and Continuous Action Representation for Practical RL in Video
  Games
Discrete and Continuous Action Representation for Practical RL in Video Games
Olivier Delalleau
Maxim Peter
Eloi Alonso
Adrien Logut
81
53
0
23 Dec 2019
The Usual Suspects? Reassessing Blame for VAE Posterior Collapse
The Usual Suspects? Reassessing Blame for VAE Posterior Collapse
Bin Dai
Ziyu Wang
David Wipf
DRL
97
76
0
23 Dec 2019
Algorithm Unrolling: Interpretable, Efficient Deep Learning for Signal
  and Image Processing
Algorithm Unrolling: Interpretable, Efficient Deep Learning for Signal and Image Processing
V. Monga
Yuelong Li
Yonina C. Eldar
130
1,027
0
22 Dec 2019
Invertible Gaussian Reparameterization: Revisiting the Gumbel-Softmax
Invertible Gaussian Reparameterization: Revisiting the Gumbel-Softmax
Andres Potapczynski
Gabriel Loaiza-Ganem
John P. Cunningham
109
30
0
19 Dec 2019
C-Flow: Conditional Generative Flow Models for Images and 3D Point
  Clouds
C-Flow: Conditional Generative Flow Models for Images and 3D Point Clouds
Albert Pumarola
S. Popov
Francesc Moreno-Noguer
V. Ferrari
3DPCAI4CE
156
80
0
15 Dec 2019
Bayesian Variational Autoencoders for Unsupervised Out-of-Distribution
  Detection
Bayesian Variational Autoencoders for Unsupervised Out-of-Distribution Detection
Erik A. Daxberger
José Miguel Hernández-Lobato
UQCV
103
63
0
11 Dec 2019
Multimodal Generative Models for Compositional Representation Learning
Multimodal Generative Models for Compositional Representation Learning
Mike Wu
Noah D. Goodman
GANDRL
97
17
0
11 Dec 2019
InfoCNF: An Efficient Conditional Continuous Normalizing Flow with
  Adaptive Solvers
InfoCNF: An Efficient Conditional Continuous Normalizing Flow with Adaptive Solvers
T. Nguyen
Animesh Garg
Richard G. Baraniuk
Anima Anandkumar
TPM
111
9
0
09 Dec 2019
Efficient Black-box Assessment of Autonomous Vehicle Safety
Efficient Black-box Assessment of Autonomous Vehicle Safety
J. Norden
Matthew O'Kelly
Aman Sinha
89
66
0
08 Dec 2019
Neural Networks with Cheap Differential Operators
Neural Networks with Cheap Differential Operators
Ricky T. Q. Chen
David Duvenaud
67
35
0
08 Dec 2019
Normalizing Flows for Probabilistic Modeling and Inference
Normalizing Flows for Probabilistic Modeling and Inference
George Papamakarios
Eric T. Nalisnick
Danilo Jimenez Rezende
S. Mohamed
Balaji Lakshminarayanan
TPMAI4CE
219
1,724
0
05 Dec 2019
Learning Multi-layer Latent Variable Model via Variational Optimization
  of Short Run MCMC for Approximate Inference
Learning Multi-layer Latent Variable Model via Variational Optimization of Short Run MCMC for Approximate Inference
Erik Nijkamp
Bo Pang
Tian Han
Linqi Zhou
Song-Chun Zhu
Ying Nian Wu
BDLDRL
89
2
0
04 Dec 2019
A Machine Learning Framework for Solving High-Dimensional Mean Field
  Game and Mean Field Control Problems
A Machine Learning Framework for Solving High-Dimensional Mean Field Game and Mean Field Control Problems
Lars Ruthotto
Stanley Osher
Wuchen Li
L. Nurbekyan
Samy Wu Fung
AI4CE
178
220
0
04 Dec 2019
WaveFlow: A Compact Flow-based Model for Raw Audio
WaveFlow: A Compact Flow-based Model for Raw Audio
Ming-Yu Liu
Kainan Peng
Kexin Zhao
Z. Song
102
117
0
03 Dec 2019
Flow Contrastive Estimation of Energy-Based Models
Flow Contrastive Estimation of Energy-Based Models
Ruiqi Gao
Erik Nijkamp
Diederik P. Kingma
Zhen Xu
Andrew M. Dai
Ying Nian Wu
GAN
101
115
0
02 Dec 2019
Learning Likelihoods with Conditional Normalizing Flows
Learning Likelihoods with Conditional Normalizing Flows
Christina Winkler
Daniel E. Worrall
Emiel Hoogeboom
Max Welling
TPM
309
227
0
29 Nov 2019
Self-attention with Functional Time Representation Learning
Self-attention with Functional Time Representation Learning
Da Xu
Chuanwei Ruan
Sushant Kumar
Evren Körpeoglu
Kannan Achan
AI4TS
82
118
0
28 Nov 2019
Mixed-curvature Variational Autoencoders
Mixed-curvature Variational Autoencoders
Ondrej Skopek
O. Ganea
Gary Bécigneul
CMLDRLBDL
76
102
0
19 Nov 2019
Rate-Regularization and Generalization in VAEs
Rate-Regularization and Generalization in VAEs
Alican Bozkurt
Babak Esmaeili
Jean-Baptiste Tristan
Dana H. Brooks
Jennifer G. Dy
Jan-Willem van de Meent
DRL
92
8
0
11 Nov 2019
Machine learning for molecular simulation
Machine learning for molecular simulation
Frank Noé
A. Tkatchenko
K. Müller
C. Clementi
AI4CE
90
668
0
07 Nov 2019
Statistical Inference in Mean-Field Variational Bayes
Statistical Inference in Mean-Field Variational Bayes
Wei Han
Yun Yang
48
18
0
04 Nov 2019
The frontier of simulation-based inference
The frontier of simulation-based inference
Kyle Cranmer
Johann Brehmer
Gilles Louppe
AI4CE
271
857
0
04 Nov 2019
Convolutional Conditional Neural Processes
Convolutional Conditional Neural Processes
Jonathan Gordon
W. Bruinsma
Andrew Y. K. Foong
James Requeima
Yann Dubois
Richard Turner
BDL
94
168
0
29 Oct 2019
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