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Variational Inference with Normalizing Flows

Variational Inference with Normalizing Flows

21 May 2015
Danilo Jimenez Rezende
S. Mohamed
    DRL
    BDL
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Papers citing "Variational Inference with Normalizing Flows"

50 / 856 papers shown
Title
Predictive Coding for Locally-Linear Control
Predictive Coding for Locally-Linear Control
Rui Shu
Tung D. Nguyen
Yinlam Chow
Tu Pham
Khoat Than
Mohammad Ghavamzadeh
Stefano Ermon
Hung Bui
OffRL
BDL
42
24
0
02 Mar 2020
Batch Stationary Distribution Estimation
Batch Stationary Distribution Estimation
Junfeng Wen
Bo Dai
Lihong Li
Dale Schuurmans
OffRL
22
22
0
02 Mar 2020
On Feature Normalization and Data Augmentation
On Feature Normalization and Data Augmentation
Boyi Li
Felix Wu
Ser-Nam Lim
Serge J. Belongie
Kilian Q. Weinberger
21
134
0
25 Feb 2020
Amortised Learning by Wake-Sleep
Amortised Learning by Wake-Sleep
W. Li
Theodore H. Moskovitz
Heishiro Kanagawa
M. Sahani
OOD
23
7
0
22 Feb 2020
Inductive Representation Learning on Temporal Graphs
Inductive Representation Learning on Temporal Graphs
Da Xu
Chuanwei Ruan
Evren Körpeoglu
Sushant Kumar
Kannan Achan
AI4CE
23
610
0
19 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
83
87
0
18 Feb 2020
Deep Gaussian Markov Random Fields
Deep Gaussian Markov Random Fields
Per Sidén
Fredrik Lindsten
BDL
28
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
31
87
0
17 Feb 2020
Stochastic Normalizing Flows
Stochastic Normalizing Flows
Hao Wu
Jonas Köhler
Frank Noé
57
176
0
16 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
29
163
0
09 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
39
52
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
66
426
0
26 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
16
107
0
15 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
26
31
0
13 Jan 2020
A Probability Density Theory for Spin-Glass Systems
A Probability Density Theory for Spin-Glass Systems
Gavin Hartnett
Masoud Mohseni
16
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
19
52
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
24
75
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
46
1,000
0
22 Dec 2019
Invertible Gaussian Reparameterization: Revisiting the Gumbel-Softmax
Invertible Gaussian Reparameterization: Revisiting the Gumbel-Softmax
Andres Potapczynski
G. Loaiza-Ganem
John P. Cunningham
32
29
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
3DPC
AI4CE
31
80
0
15 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
28
9
0
09 Dec 2019
Getting Topology and Point Cloud Generation to Mesh
Getting Topology and Point Cloud Generation to Mesh
Austin Dill
Chun-Liang Li
Songwei Ge
Eunsu Kang
3DPC
25
3
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
TPM
AI4CE
57
1,631
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
BDL
DRL
19
2
0
04 Dec 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
23
114
0
28 Nov 2019
Mixed-curvature Variational Autoencoders
Mixed-curvature Variational Autoencoders
Ondrej Skopek
O. Ganea
Gary Bécigneul
CML
DRL
BDL
30
101
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
38
7
0
11 Nov 2019
Machine learning for molecular simulation
Machine learning for molecular simulation
Frank Noé
A. Tkatchenko
K. Müller
C. Clementi
AI4CE
16
642
0
07 Nov 2019
Scalable Variational Gaussian Processes for Crowdsourcing: Glitch
  Detection in LIGO
Scalable Variational Gaussian Processes for Crowdsourcing: Glitch Detection in LIGO
Pablo Morales-Álvarez
Pablo Ruiz
S. Coughlin
Rafael Molina
Aggelos K. Katsaggelos
21
14
0
05 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
25
162
0
29 Oct 2019
Weight of Evidence as a Basis for Human-Oriented Explanations
Weight of Evidence as a Basis for Human-Oriented Explanations
David Alvarez-Melis
Hal Daumé
Jennifer Wortman Vaughan
Hanna M. Wallach
XAI
FAtt
24
20
0
29 Oct 2019
On Investigation of Unsupervised Speech Factorization Based on
  Normalization Flow
On Investigation of Unsupervised Speech Factorization Based on Normalization Flow
Haoran Sun
Yunqi Cai
Lantian Li
Dong Wang
21
1
0
29 Oct 2019
Discrete Residual Flow for Probabilistic Pedestrian Behavior Prediction
Discrete Residual Flow for Probabilistic Pedestrian Behavior Prediction
Ajay Jain
Sergio Casas
Renjie Liao
Yuwen Xiong
Song Feng
Sean Segal
R. Urtasun
156
73
0
17 Oct 2019
MAVEN: Multi-Agent Variational Exploration
MAVEN: Multi-Agent Variational Exploration
Anuj Mahajan
Tabish Rashid
Mikayel Samvelyan
Shimon Whiteson
DRL
146
355
0
16 Oct 2019
The Neural Moving Average Model for Scalable Variational Inference of
  State Space Models
The Neural Moving Average Model for Scalable Variational Inference of State Space Models
Tom Ryder
D. Prangle
Andrew Golightly
Isaac Matthews
BDL
AI4TS
16
6
0
02 Oct 2019
Relaxing Bijectivity Constraints with Continuously Indexed Normalising
  Flows
Relaxing Bijectivity Constraints with Continuously Indexed Normalising Flows
R. Cornish
Anthony L. Caterini
George Deligiannidis
Arnaud Doucet
22
2
0
30 Sep 2019
Hamiltonian Generative Networks
Hamiltonian Generative Networks
Peter Toth
Danilo Jimenez Rezende
Andrew Jaegle
S. Racanière
Aleksandar Botev
I. Higgins
BDL
DRL
AI4CE
GAN
21
216
0
30 Sep 2019
Wasserstein-2 Generative Networks
Wasserstein-2 Generative Networks
Alexander Korotin
Vage Egiazarian
Arip Asadulaev
Alexander Safin
E. Burnaev
GAN
131
101
0
28 Sep 2019
Intensity-Free Learning of Temporal Point Processes
Intensity-Free Learning of Temporal Point Processes
Oleksandr Shchur
Marin Bilos
Stephan Günnemann
AI4TS
27
167
0
26 Sep 2019
$ρ$-VAE: Autoregressive parametrization of the VAE encoder
ρρρ-VAE: Autoregressive parametrization of the VAE encoder
Sohrab Ferdowsi
M. Diephuis
Shideh Rezaeifar
Slava Voloshynovskiy
11
3
0
13 Sep 2019
Balancing Reconstruction Quality and Regularisation in ELBO for VAEs
Balancing Reconstruction Quality and Regularisation in ELBO for VAEs
Shuyu Lin
Stephen J. Roberts
Niki Trigoni
R. Clark
DRL
21
15
0
09 Sep 2019
A Surprisingly Effective Fix for Deep Latent Variable Modeling of Text
A Surprisingly Effective Fix for Deep Latent Variable Modeling of Text
Bohan Li
Junxian He
Graham Neubig
Taylor Berg-Kirkpatrick
Yiming Yang
DRL
11
70
0
02 Sep 2019
PixelVAE++: Improved PixelVAE with Discrete Prior
PixelVAE++: Improved PixelVAE with Discrete Prior
Hossein Sadeghi
Evgeny Andriyash
W. Vinci
L. Buffoni
Mohammad H. Amin
BDL
DRL
21
33
0
26 Aug 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
BDL
DRL
AI4TS
27
84
0
24 Aug 2019
DUAL-GLOW: Conditional Flow-Based Generative Model for Modality Transfer
DUAL-GLOW: Conditional Flow-Based Generative Model for Modality Transfer
Haoliang Sun
Ronak R. Mehta
H. Zhou
Z. Huang
Sterling C. Johnson
V. Prabhakaran
Vikas Singh
MedIm
31
46
0
21 Aug 2019
Unconstrained Monotonic Neural Networks
Unconstrained Monotonic Neural Networks
Antoine Wehenkel
Gilles Louppe
TPM
31
146
0
14 Aug 2019
Probabilistic Residual Learning for Aleatoric Uncertainty in Image Restoration
Chen Zhang
Bangti Jin
UQCV
22
12
0
01 Aug 2019
MadMiner: Machine learning-based inference for particle physics
MadMiner: Machine learning-based inference for particle physics
Johann Brehmer
F. Kling
Irina Espejo
Kyle Cranmer
21
113
0
24 Jul 2019
Transport Monte Carlo: High-Accuracy Posterior Approximation via Random
  Transport
Transport Monte Carlo: High-Accuracy Posterior Approximation via Random Transport
L. Duan
OT
29
11
0
24 Jul 2019
The continuous Bernoulli: fixing a pervasive error in variational
  autoencoders
The continuous Bernoulli: fixing a pervasive error in variational autoencoders
G. Loaiza-Ganem
John P. Cunningham
DRL
29
83
0
16 Jul 2019
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