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Normalizing Flows for Probabilistic Modeling and Inference
v1v2 (latest)

Normalizing Flows for Probabilistic Modeling and Inference

Journal of machine learning research (JMLR), 2019
5 December 2019
George Papamakarios
Eric T. Nalisnick
Danilo Jimenez Rezende
S. Mohamed
Balaji Lakshminarayanan
    TPMAI4CE
ArXiv (abs)PDFHTML

Papers citing "Normalizing Flows for Probabilistic Modeling and Inference"

50 / 1,115 papers shown
Structured Stochastic Gradient MCMC
Structured Stochastic Gradient MCMCInternational Conference on Machine Learning (ICML), 2021
Antonios Alexos
Alex Boyd
Stephan Mandt
BDL
283
13
0
19 Jul 2021
Equivariant Manifold Flows
Equivariant Manifold FlowsNeural Information Processing Systems (NeurIPS), 2021
Isay Katsman
Aaron Lou
Derek Lim
Qingxuan Jiang
Ser-Nam Lim
Christopher De Sa
AI4CE
151
26
0
19 Jul 2021
Efficient Bayesian Sampling Using Normalizing Flows to Assist Markov
  Chain Monte Carlo Methods
Efficient Bayesian Sampling Using Normalizing Flows to Assist Markov Chain Monte Carlo Methods
Marylou Gabrié
Grant M. Rotskoff
Eric Vanden-Eijnden
179
26
0
16 Jul 2021
Copula-Based Normalizing Flows
Copula-Based Normalizing Flows
M. Laszkiewicz
Johannes Lederer
Asja Fischer
183
7
0
15 Jul 2021
Generalization of the Change of Variables Formula with Applications to
  Residual Flows
Generalization of the Change of Variables Formula with Applications to Residual Flows
Niklas Koenen
Marvin N. Wright
Peter Maass
Jens Behrmann
144
2
0
09 Jul 2021
Likelihood-Free Frequentist Inference: Bridging Classical Statistics and
  Machine Learning for Reliable Simulator-Based Inference
Likelihood-Free Frequentist Inference: Bridging Classical Statistics and Machine Learning for Reliable Simulator-Based InferenceElectronic Journal of Statistics (EJS), 2021
Niccolò Dalmasso
Luca Masserano
David Y. Zhao
Rafael Izbicki
Ann B. Lee
654
11
0
08 Jul 2021
Structured Denoising Diffusion Models in Discrete State-Spaces
Structured Denoising Diffusion Models in Discrete State-Spaces
Jacob Austin
Daniel D. Johnson
Jonathan Ho
Daniel Tarlow
Rianne van den Berg
DiffM
843
1,362
0
07 Jul 2021
iPOKE: Poking a Still Image for Controlled Stochastic Video Synthesis
iPOKE: Poking a Still Image for Controlled Stochastic Video Synthesis
A. Blattmann
Timo Milbich
Michael Dorkenwald
Bjorn Ommer
DiffMVGen
188
48
0
06 Jul 2021
Featurized Density Ratio Estimation
Featurized Density Ratio Estimation
Kristy Choi
Madeline Liao
Stefano Ermon
TPM
159
33
0
05 Jul 2021
Learning ODEs via Diffeomorphisms for Fast and Robust Integration
Learning ODEs via Diffeomorphisms for Fast and Robust Integration
Weiming Zhi
Tin Lai
Lionel Ott
Edwin V. Bonilla
Fabio Ramos
OOD
131
4
0
04 Jul 2021
Truncated Marginal Neural Ratio Estimation
Truncated Marginal Neural Ratio Estimation
Benjamin Kurt Miller
A. Cole
Patrick Forré
Gilles Louppe
Christoph Weniger
370
47
0
02 Jul 2021
Differentiable Particle Filters through Conditional Normalizing Flow
Differentiable Particle Filters through Conditional Normalizing Flow
Xiongjie Chen
Hao Wen
Yunpeng Li
301
26
0
01 Jul 2021
Continuous Latent Process Flows
Continuous Latent Process FlowsNeural Information Processing Systems (NeurIPS), 2021
Ruizhi Deng
Marcus A. Brubaker
Greg Mori
Andreas M. Lehrmann
AI4TS
420
18
0
29 Jun 2021
A Survey on Neural Speech Synthesis
A Survey on Neural Speech Synthesis
Xu Tan
Tao Qin
Frank Soong
Tie-Yan Liu
AI4TS
349
435
0
29 Jun 2021
Flexible Variational Bayes based on a Copula of a Mixture
Flexible Variational Bayes based on a Copula of a MixtureJournal of Computational And Graphical Statistics (JCGS), 2021
David Gunawan
Robert Kohn
David J. Nott
350
13
0
28 Jun 2021
Transflower: probabilistic autoregressive dance generation with
  multimodal attention
Transflower: probabilistic autoregressive dance generation with multimodal attentionACM Transactions on Graphics (TOG), 2021
Guillermo Valle Pérez
G. Henter
Jonas Beskow
A. Holzapfel
Pierre-Yves Oudeyer
Simon Alexanderson
374
48
0
25 Jun 2021
On Incorporating Inductive Biases into VAEs
On Incorporating Inductive Biases into VAEsInternational Conference on Learning Representations (ICLR), 2021
Ning Miao
Emile Mathieu
N. Siddharth
Yee Whye Teh
Tom Rainforth
CMLDRL
258
11
0
25 Jun 2021
NP-DRAW: A Non-Parametric Structured Latent Variable Model for Image
  Generation
NP-DRAW: A Non-Parametric Structured Latent Variable Model for Image Generation
Xiaohui Zeng
R. Urtasun
R. Zemel
Sanja Fidler
Renjie Liao
DiffM
123
2
0
25 Jun 2021
Task-agnostic Continual Learning with Hybrid Probabilistic Models
Task-agnostic Continual Learning with Hybrid Probabilistic Models
Polina Kirichenko
Mehrdad Farajtabar
Dushyant Rao
Balaji Lakshminarayanan
Nir Levine
Ang Li
Huiyi Hu
A. Wilson
Razvan Pascanu
VLMBDLCLL
139
23
0
24 Jun 2021
Black Box Variational Bayesian Model Averaging
Black Box Variational Bayesian Model Averaging
Vojtech Kejzlar
Shrijita Bhattacharya
Mookyong Son
T. Maiti
BDL
222
3
0
23 Jun 2021
ADAVI: Automatic Dual Amortized Variational Inference Applied To
  Pyramidal Bayesian Models
ADAVI: Automatic Dual Amortized Variational Inference Applied To Pyramidal Bayesian Models
Louis Rouillard
Demian Wassermann
187
2
0
23 Jun 2021
Riemannian Convex Potential Maps
Riemannian Convex Potential MapsInternational Conference on Machine Learning (ICML), 2021
Samuel N. Cohen
Brandon Amos
Y. Lipman
220
24
0
18 Jun 2021
Causal Bias Quantification for Continuous Treatments
Causal Bias Quantification for Continuous Treatments
Gianluca Detommaso
Michael Bruckner
Philip Schulz
Victor Chernozhukov
CML
255
0
0
17 Jun 2021
A deep generative model for probabilistic energy forecasting in power
  systems: normalizing flows
A deep generative model for probabilistic energy forecasting in power systems: normalizing flowsApplied Energy (Appl. Energy), 2021
Jonathan Dumas
Antoine Wehenkel
Bertrand Cornélusse
Antonio Sutera
AI4TS
455
95
0
17 Jun 2021
A Simple Fix to Mahalanobis Distance for Improving Near-OOD Detection
A Simple Fix to Mahalanobis Distance for Improving Near-OOD Detection
Jie Jessie Ren
Stanislav Fort
J. Liu
Abhijit Guha Roy
Shreyas Padhy
Balaji Lakshminarayanan
UQCV
418
269
0
16 Jun 2021
A Flow-Based Neural Network for Time Domain Speech Enhancement
A Flow-Based Neural Network for Time Domain Speech Enhancement
Martin Strauss
B. Edler
180
39
0
16 Jun 2021
Invertible Attention
Invertible Attention
Jiajun Zha
Yiran Zhong
Jing Zhang
Leonid Sigal
Liang Zheng
174
7
0
16 Jun 2021
Improving the expressiveness of neural vocoding with non-affine
  Normalizing Flows
Improving the expressiveness of neural vocoding with non-affine Normalizing Flows
Adam Gabry's
Yunlong Jiao
V. Klimkov
Daniel Korzekwa
Roberto Barra-Chicote
150
1
0
16 Jun 2021
Multi-Resolution Continuous Normalizing Flows
Multi-Resolution Continuous Normalizing Flows
Vikram S. Voleti
Chris Finlay
Adam M. Oberman
Christopher Pal
385
6
0
15 Jun 2021
The DEformer: An Order-Agnostic Distribution Estimating Transformer
The DEformer: An Order-Agnostic Distribution Estimating Transformer
Michael A. Alcorn
Anh Totti Nguyen
208
5
0
13 Jun 2021
Harmonization with Flow-based Causal Inference
Harmonization with Flow-based Causal InferenceInternational Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2021
Rongguang Wang
Pratik Chaudhari
Christos Davatzikos
OODCML
160
28
0
12 Jun 2021
Quantum Speedup of Natural Gradient for Variational Bayes
Quantum Speedup of Natural Gradient for Variational Bayes
A. Lopatnikova
Minh-Ngoc Tran
BDL
359
3
0
10 Jun 2021
CaloFlow: Fast and Accurate Generation of Calorimeter Showers with
  Normalizing Flows
CaloFlow: Fast and Accurate Generation of Calorimeter Showers with Normalizing Flows
Claudius Krause
David Shih
AI4CE
359
90
0
09 Jun 2021
Tractable Density Estimation on Learned Manifolds with Conformal
  Embedding Flows
Tractable Density Estimation on Learned Manifolds with Conformal Embedding FlowsNeural Information Processing Systems (NeurIPS), 2021
Brendan Leigh Ross
Jesse C. Cresswell
TPM
258
35
0
09 Jun 2021
I Don't Need u: Identifiable Non-Linear ICA Without Side Information
I Don't Need u: Identifiable Non-Linear ICA Without Side Information
M. Willetts
Brooks Paige
CMLOOD
280
26
0
09 Jun 2021
Independent mechanism analysis, a new concept?
Independent mechanism analysis, a new concept?Neural Information Processing Systems (NeurIPS), 2021
Luigi Gresele
Julius von Kügelgen
Vincent Stimper
Bernhard Schölkopf
M. Besserve
CML
339
113
0
09 Jun 2021
Marginalizable Density Models
Marginalizable Density Models
D. Gilboa
Ari Pakman
Thibault Vatter
BDL
171
5
0
08 Jun 2021
Self-Supervised Learning with Data Augmentations Provably Isolates
  Content from Style
Self-Supervised Learning with Data Augmentations Provably Isolates Content from StyleNeural Information Processing Systems (NeurIPS), 2021
Julius von Kügelgen
Yash Sharma
Luigi Gresele
Wieland Brendel
Bernhard Schölkopf
M. Besserve
Francesco Locatello
375
356
0
08 Jun 2021
Scalable conditional deep inverse Rosenblatt transports using
  tensor-trains and gradient-based dimension reduction
Scalable conditional deep inverse Rosenblatt transports using tensor-trains and gradient-based dimension reductionJournal of Computational Physics (JCP), 2021
Tiangang Cui
S. Dolgov
O. Zahm
242
18
0
08 Jun 2021
Concave Utility Reinforcement Learning: the Mean-Field Game Viewpoint
Concave Utility Reinforcement Learning: the Mean-Field Game ViewpointAdaptive Agents and Multi-Agent Systems (AAMAS), 2021
Matthieu Geist
Julien Pérolat
Mathieu Laurière
Romuald Elie
Sarah Perrin
Olivier Bachem
Rémi Munos
Olivier Pietquin
282
69
0
07 Jun 2021
Density estimation on smooth manifolds with normalizing flows
Density estimation on smooth manifolds with normalizing flows
Dimitris Kalatzis
J. Z. Ye
Alison Pouplin
Jesper Wohlert
Søren Hauberg
210
6
0
07 Jun 2021
Evaluating State-of-the-Art Classification Models Against Bayes
  Optimality
Evaluating State-of-the-Art Classification Models Against Bayes OptimalityNeural Information Processing Systems (NeurIPS), 2021
Ryan Theisen
Huan Wang
Lav Varshney
Caiming Xiong
R. Socher
112
18
0
07 Jun 2021
Semi-Empirical Objective Functions for MCMC Proposal Optimization
Semi-Empirical Objective Functions for MCMC Proposal OptimizationInternational Conference on Pattern Recognition (ICPR), 2021
Chris Cannella
Vahid Tarokh
316
1
0
03 Jun 2021
Semi-supervised Learning with Missing Values Imputation
Semi-supervised Learning with Missing Values ImputationKnowledge-Based Systems (KBS), 2021
Buliao Huang
Yunhui Zhu
Muhammad Usman
Huanhuan Chen
181
14
0
03 Jun 2021
Normalizing Flows for Knockoff-free Controlled Feature Selection
Normalizing Flows for Knockoff-free Controlled Feature SelectionNeural Information Processing Systems (NeurIPS), 2021
Derek Hansen
Brian Manzo
Jeffrey Regier
OOD
233
6
0
03 Jun 2021
Rectangular Flows for Manifold Learning
Rectangular Flows for Manifold LearningNeural Information Processing Systems (NeurIPS), 2021
M. Volkovs
Gabriel Loaiza-Ganem
Geoff Pleiss
John P. Cunningham
DRL
334
51
0
02 Jun 2021
Improving Compositionality of Neural Networks by Decoding
  Representations to Inputs
Improving Compositionality of Neural Networks by Decoding Representations to InputsNeural Information Processing Systems (NeurIPS), 2021
Mike Wu
Noah D. Goodman
Stefano Ermon
AI4CE
124
3
0
01 Jun 2021
Parallelized Computation and Backpropagation Under Angle-Parametrized
  Orthogonal Matrices
Parallelized Computation and Backpropagation Under Angle-Parametrized Orthogonal Matrices
F. Hamze
148
1
0
30 May 2021
A Probabilistic Forecast-Driven Strategy for a Risk-Aware Participation
  in the Capacity Firming Market: extended version
A Probabilistic Forecast-Driven Strategy for a Risk-Aware Participation in the Capacity Firming Market: extended versionIEEE Transactions on Sustainable Energy (IEEE Trans. Sustain. Energy), 2021
Jonathan Dumas
Colin Cointe
Antoine Wehenkel
Antonio Sutera
X. Fettweis
Bertrand Cornélusse
140
10
0
28 May 2021
Density estimation on low-dimensional manifolds: an inflation-deflation
  approach
Density estimation on low-dimensional manifolds: an inflation-deflation approachJournal of machine learning research (JMLR), 2021
Christian Horvat
J. Pfister
255
16
0
25 May 2021
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