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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

17 February 2020
Chin-Wei Huang
Laurent Dinh
Aaron Courville
    DRL
ArXivPDFHTML

Papers citing "Augmented Normalizing Flows: Bridging the Gap Between Generative Flows and Latent Variable Models"

50 / 67 papers shown
Title
FRIREN: Beyond Trajectories -- A Spectral Lens on Time
FRIREN: Beyond Trajectories -- A Spectral Lens on Time
Qilin Wang
AI4TS
23
0
0
23 May 2025
TRADE: Transfer of Distributions between External Conditions with Normalizing Flows
TRADE: Transfer of Distributions between External Conditions with Normalizing Flows
Stefan Wahl
Armand Rousselot
Felix Dräxler
Ullrich Kothe
Ullrich Köthe
84
0
0
25 Oct 2024
A Survey of Geometric Graph Neural Networks: Data Structures, Models and Applications
A Survey of Geometric Graph Neural Networks: Data Structures, Models and Applications
Jiaqi Han
Jiacheng Cen
Liming Wu
Zongzhao Li
Xiangzhe Kong
...
Zhewei Wei
Deli Zhao
Yu Rong
Wenbing Huang
Wenbing Huang
AI4CE
81
23
0
01 Mar 2024
Variational Autoencoders with Normalizing Flow Decoders
Variational Autoencoders with Normalizing Flow Decoders
Rogan Morrow
Wei-Chen Chiu
DRL
19
19
0
12 Apr 2020
SUMO: Unbiased Estimation of Log Marginal Probability for Latent
  Variable Models
SUMO: Unbiased Estimation of Log Marginal Probability for Latent Variable Models
Yucen Luo
Alex Beatson
Mohammad Norouzi
Jun Zhu
David Duvenaud
Ryan P. Adams
Ricky T. Q. Chen
88
29
0
01 Apr 2020
Decision-Making with Auto-Encoding Variational Bayes
Decision-Making with Auto-Encoding Variational Bayes
Romain Lopez
Pierre Boyeau
Nir Yosef
Michael I. Jordan
Jeffrey Regier
BDL
138
10,591
0
17 Feb 2020
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
TPM
AI4CE
120
1,662
0
05 Dec 2019
Set Flow: A Permutation Invariant Normalizing Flow
Set Flow: A Permutation Invariant Normalizing Flow
Kashif Rasul
Ingmar Schuster
Roland Vollgraf
Urs M. Bergmann
BDL
3DPC
DRL
32
5
0
06 Sep 2019
Accelerated Information Gradient flow
Accelerated Information Gradient flow
Yifei Wang
Wuchen Li
55
56
0
04 Sep 2019
Normalizing Flows: An Introduction and Review of Current Methods
Normalizing Flows: An Introduction and Review of Current Methods
I. Kobyzev
S. Prince
Marcus A. Brubaker
TPM
MedIm
30
57
0
25 Aug 2019
MintNet: Building Invertible Neural Networks with Masked Convolutions
MintNet: Building Invertible Neural Networks with Masked Convolutions
Yang Song
Chenlin Meng
Stefano Ermon
31
68
0
18 Jul 2019
Stochastic Neural Network with Kronecker Flow
Stochastic Neural Network with Kronecker Flow
Chin-Wei Huang
Ahmed Touati
Pascal Vincent
Gintare Karolina Dziugaite
Alexandre Lacoste
Aaron Courville
BDL
41
8
0
10 Jun 2019
Improving Exploration in Soft-Actor-Critic with Normalizing Flows
  Policies
Improving Exploration in Soft-Actor-Critic with Normalizing Flows Policies
Patrick Nadeem Ward
Ariella Smofsky
A. Bose
21
58
0
06 Jun 2019
Residual Flows for Invertible Generative Modeling
Residual Flows for Invertible Generative Modeling
Ricky T. Q. Chen
Jens Behrmann
David Duvenaud
J. Jacobsen
BDL
TPM
DRL
40
375
0
06 Jun 2019
Leveraging exploration in off-policy algorithms via normalizing flows
Leveraging exploration in off-policy algorithms via normalizing flows
Bogdan Mazoure
T. Doan
A. Durand
R. Devon Hjelm
Joelle Pineau
OnRL
42
60
0
16 May 2019
Semi-Conditional Normalizing Flows for Semi-Supervised Learning
Semi-Conditional Normalizing Flows for Semi-Supervised Learning
Andrei Atanov
Alexandra Volokhova
Arsenii Ashukha
Ivan Sosnovik
Dmitry Vetrov
BDL
38
42
0
01 May 2019
Augmented Neural ODEs
Augmented Neural ODEs
Emilien Dupont
Arnaud Doucet
Yee Whye Teh
BDL
54
622
0
02 Apr 2019
MaCow: Masked Convolutional Generative Flow
MaCow: Masked Convolutional Generative Flow
Xuezhe Ma
Xiang Kong
Shanghang Zhang
Eduard H. Hovy
DRL
38
66
0
12 Feb 2019
Hybrid Models with Deep and Invertible Features
Hybrid Models with Deep and Invertible Features
Eric T. Nalisnick
Akihiro Matsukawa
Yee Whye Teh
Dilan Görür
Balaji Lakshminarayanan
BDL
DRL
49
99
0
07 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
BDL
DRL
37
213
0
06 Feb 2019
Flow++: Improving Flow-Based Generative Models with Variational
  Dequantization and Architecture Design
Flow++: Improving Flow-Based Generative Models with Variational Dequantization and Architecture Design
Jonathan Ho
Xi Chen
A. Srinivas
Yan Duan
Pieter Abbeel
DRL
35
446
0
01 Feb 2019
Emerging Convolutions for Generative Normalizing Flows
Emerging Convolutions for Generative Normalizing Flows
Emiel Hoogeboom
Rianne van den Berg
Max Welling
DRL
38
98
0
30 Jan 2019
Generating High Fidelity Images with Subscale Pixel Networks and
  Multidimensional Upscaling
Generating High Fidelity Images with Subscale Pixel Networks and Multidimensional Upscaling
Jacob Menick
Nal Kalchbrenner
43
150
0
04 Dec 2018
Invertible Residual Networks
Invertible Residual Networks
Jens Behrmann
Will Grathwohl
Ricky T. Q. Chen
David Duvenaud
J. Jacobsen
UQCV
TPM
67
621
0
02 Nov 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
44
861
0
02 Oct 2018
Glow: Generative Flow with Invertible 1x1 Convolutions
Glow: Generative Flow with Invertible 1x1 Convolutions
Diederik P. Kingma
Prafulla Dhariwal
BDL
DRL
189
3,110
0
09 Jul 2018
Neural Ordinary Differential Equations
Neural Ordinary Differential Equations
T. Chen
Yulia Rubanova
J. Bettencourt
David Duvenaud
AI4CE
193
5,024
0
19 Jun 2018
Autoregressive Quantile Networks for Generative Modeling
Autoregressive Quantile Networks for Generative Modeling
Georg Ostrovski
Will Dabney
Rémi Munos
DRL
44
87
0
14 Jun 2018
Neural Autoregressive Flows
Neural Autoregressive Flows
Chin-Wei Huang
David M. Krueger
Alexandre Lacoste
Aaron Courville
DRL
AI4CE
66
436
0
03 Apr 2018
Sylvester Normalizing Flows for Variational Inference
Sylvester Normalizing Flows for Variational Inference
Rianne van den Berg
Leonard Hasenclever
Jakub M. Tomczak
Max Welling
BDL
DRL
36
249
0
15 Mar 2018
Hierarchical Adversarially Learned Inference
Hierarchical Adversarially Learned Inference
Mohamed Ishmael Belghazi
Sai Rajeswar
Olivier Mastropietro
Negar Rostamzadeh
Jovana Mitrović
Aaron Courville
GAN
BDL
56
29
0
04 Feb 2018
Inference Suboptimality in Variational Autoencoders
Inference Suboptimality in Variational Autoencoders
Chris Cremer
Xuechen Li
David Duvenaud
DRL
BDL
63
281
0
10 Jan 2018
PixelSNAIL: An Improved Autoregressive Generative Model
PixelSNAIL: An Improved Autoregressive Generative Model
Xi Chen
Nikhil Mishra
Mostafa Rohaninejad
Pieter Abbeel
DRL
DiffM
BDL
GAN
48
270
0
28 Dec 2017
Parallel WaveNet: Fast High-Fidelity Speech Synthesis
Parallel WaveNet: Fast High-Fidelity Speech Synthesis
Aaron van den Oord
Yazhe Li
Igor Babuschkin
Karen Simonyan
Oriol Vinyals
...
Alex Graves
Helen King
T. Walters
Dan Belov
Demis Hassabis
114
857
0
28 Nov 2017
Generalizing Hamiltonian Monte Carlo with Neural Networks
Generalizing Hamiltonian Monte Carlo with Neural Networks
Daniel Levy
Matthew D. Hoffman
Jascha Narain Sohl-Dickstein
BDL
36
130
0
25 Nov 2017
Bayesian Hypernetworks
Bayesian Hypernetworks
David M. Krueger
Chin-Wei Huang
Riashat Islam
Ryan Turner
Alexandre Lacoste
Aaron Courville
UQCV
BDL
44
139
0
13 Oct 2017
Learnable Explicit Density for Continuous Latent Space and Variational
  Inference
Learnable Explicit Density for Continuous Latent Space and Variational Inference
Chin-Wei Huang
Ahmed Touati
Laurent Dinh
M. Drozdzal
Mohammad Havaei
Laurent Charlin
Aaron Courville
BDL
DRL
60
28
0
06 Oct 2017
The Reversible Residual Network: Backpropagation Without Storing
  Activations
The Reversible Residual Network: Backpropagation Without Storing Activations
Aidan Gomez
Mengye Ren
R. Urtasun
Roger C. Grosse
50
545
0
14 Jul 2017
A-NICE-MC: Adversarial Training for MCMC
A-NICE-MC: Adversarial Training for MCMC
Jiaming Song
Shengjia Zhao
Stefano Ermon
BDL
OOD
54
109
0
23 Jun 2017
Masked Autoregressive Flow for Density Estimation
Masked Autoregressive Flow for Density Estimation
George Papamakarios
Theo Pavlakou
Iain Murray
111
1,340
0
19 May 2017
Improved Training of Wasserstein GANs
Improved Training of Wasserstein GANs
Ishaan Gulrajani
Faruk Ahmed
Martín Arjovsky
Vincent Dumoulin
Aaron Courville
GAN
107
9,509
0
31 Mar 2017
Parallel Multiscale Autoregressive Density Estimation
Parallel Multiscale Autoregressive Density Estimation
Scott E. Reed
Aaron van den Oord
Nal Kalchbrenner
Sergio Gomez Colmenarejo
Ziyun Wang
Dan Belov
Nando de Freitas
BDL
55
204
0
10 Mar 2017
Multiplicative Normalizing Flows for Variational Bayesian Neural
  Networks
Multiplicative Normalizing Flows for Variational Bayesian Neural Networks
Christos Louizos
Max Welling
BDL
127
456
0
06 Mar 2017
Calibrating Energy-based Generative Adversarial Networks
Calibrating Energy-based Generative Adversarial Networks
Zihang Dai
Amjad Almahairi
Philip Bachman
Eduard H. Hovy
Aaron Courville
GAN
35
110
0
06 Feb 2017
Improving Variational Auto-Encoders using Householder Flow
Improving Variational Auto-Encoders using Householder Flow
Jakub M. Tomczak
Max Welling
BDL
DRL
49
174
0
29 Nov 2016
Deep Variational Inference Without Pixel-Wise Reconstruction
Deep Variational Inference Without Pixel-Wise Reconstruction
Siddharth Agrawal
Ambedkar Dukkipati
DRL
3DV
BDL
37
13
0
16 Nov 2016
PixelVAE: A Latent Variable Model for Natural Images
PixelVAE: A Latent Variable Model for Natural Images
Ishaan Gulrajani
Kundan Kumar
Faruk Ahmed
Adrien Ali Taïga
Francesco Visin
David Vazquez
Aaron Courville
DRL
SSL
BDL
49
340
0
15 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
105
672
0
08 Nov 2016
Generative Adversarial Networks as Variational Training of Energy Based
  Models
Generative Adversarial Networks as Variational Training of Energy Based Models
Shuangfei Zhai
Yu Cheng
Rogerio Feris
Zhongfei Zhang
GAN
19
30
0
06 Nov 2016
Conditional Image Generation with PixelCNN Decoders
Conditional Image Generation with PixelCNN Decoders
Aaron van den Oord
Nal Kalchbrenner
Oriol Vinyals
L. Espeholt
Alex Graves
Koray Kavukcuoglu
VLM
115
2,490
0
16 Jun 2016
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