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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
Density-Softmax: Efficient Test-time Model for Uncertainty Estimation
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H. Bui
Anqi Liu
OODUQCV
589
9
0
13 Feb 2023
Diffusion Models in Bioinformatics: A New Wave of Deep Learning
  Revolution in Action
Diffusion Models in Bioinformatics: A New Wave of Deep Learning Revolution in Action
Zhiye Guo
Jian Liu
Yanli Wang
Mengrui Chen
Duolin Wang
Dong Xu
Jianlin Cheng
MedImAI4CEDiffM
241
26
0
13 Feb 2023
Variational Mixture of HyperGenerators for Learning Distributions Over
  Functions
Variational Mixture of HyperGenerators for Learning Distributions Over FunctionsInternational Conference on Machine Learning (ICML), 2023
Batuhan Koyuncu
Pablo Sánchez-Martín
I. Peis
Pablo M. Olmos
Isabel Valera
BDLGANDRL
224
6
0
13 Feb 2023
Variational Bayesian Neural Networks via Resolution of Singularities
Variational Bayesian Neural Networks via Resolution of SingularitiesJournal of Computational And Graphical Statistics (JCGS), 2023
Susan Wei
Edmund Lau
BDL
248
3
0
13 Feb 2023
On Sampling with Approximate Transport Maps
On Sampling with Approximate Transport MapsInternational Conference on Machine Learning (ICML), 2023
Louis Grenioux
Alain Durmus
Eric Moulines
Marylou Gabrié
OT
315
23
0
09 Feb 2023
Federated Variational Inference Methods for Structured Latent Variable
  Models
Federated Variational Inference Methods for Structured Latent Variable Models
Conor Hassan
Roberto Salomone
Kerrie Mengersen
BDLFedML
315
5
0
07 Feb 2023
Sampling-Based Accuracy Testing of Posterior Estimators for General
  Inference
Sampling-Based Accuracy Testing of Posterior Estimators for General InferenceInternational Conference on Machine Learning (ICML), 2023
Pablo Lemos
A. Coogan
Y. Hezaveh
Laurence Perreault Levasseur
285
55
0
06 Feb 2023
Counterfactual Identifiability of Bijective Causal Models
Counterfactual Identifiability of Bijective Causal ModelsInternational Conference on Machine Learning (ICML), 2023
Arash Nasr-Esfahany
MohammadIman Alizadeh
Devavrat Shah
CMLBDL
464
38
0
04 Feb 2023
Fixed-kinetic Neural Hamiltonian Flows for enhanced interpretability and reduced complexity
Fixed-kinetic Neural Hamiltonian Flows for enhanced interpretability and reduced complexityInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Vincent Souveton
Arnaud Guillin
J. Jasche
G. Lavaux
Manon Michel
259
3
0
03 Feb 2023
Normalizing Flow Ensembles for Rich Aleatoric and Epistemic Uncertainty
  Modeling
Normalizing Flow Ensembles for Rich Aleatoric and Epistemic Uncertainty ModelingAAAI Conference on Artificial Intelligence (AAAI), 2023
Lucas Berry
David Meger
296
14
0
02 Feb 2023
Unsupervised Learning of Sampling Distributions for Particle Filters
Unsupervised Learning of Sampling Distributions for Particle FiltersIEEE Transactions on Signal Processing (IEEE TSP), 2023
Fernando Gama
Nicolas Zilberstein
Martín Sevilla
Richard Baraniuk
Santiago Segarra
210
12
0
02 Feb 2023
Two for One: Diffusion Models and Force Fields for Coarse-Grained
  Molecular Dynamics
Two for One: Diffusion Models and Force Fields for Coarse-Grained Molecular DynamicsJournal of Chemical Theory and Computation (JCTC), 2023
Marloes Arts
Victor Garcia Satorras
Chin-Wei Huang
Daniel Zuegner
Marco Federici
C. Clementi
Frank Noé
Tian Xie
Rianne van den Berg
DiffM
379
117
0
01 Feb 2023
Automatically Marginalized MCMC in Probabilistic Programming
Automatically Marginalized MCMC in Probabilistic ProgrammingInternational Conference on Machine Learning (ICML), 2023
Jinlin Lai
Javier Burroni
Hui Guan
Daniel Sheldon
248
3
0
01 Feb 2023
Misspecification-robust Sequential Neural Likelihood for
  Simulation-based Inference
Misspecification-robust Sequential Neural Likelihood for Simulation-based Inference
Ryan P. Kelly
David J. Nott
David T. Frazier
D. Warne
Christopher C. Drovandi
290
13
0
31 Jan 2023
Model-based Offline Reinforcement Learning with Local Misspecification
Model-based Offline Reinforcement Learning with Local MisspecificationAAAI Conference on Artificial Intelligence (AAAI), 2023
Kefan Dong
Yannis Flet-Berliac
Allen Nie
Emma Brunskill
OffRL
206
6
0
26 Jan 2023
Rigid Body Flows for Sampling Molecular Crystal Structures
Rigid Body Flows for Sampling Molecular Crystal StructuresInternational Conference on Machine Learning (ICML), 2023
Jonas Köhler
Michele Invernizzi
P. D. Haan
Frank Noé
AI4CE
408
39
0
26 Jan 2023
normflows: A PyTorch Package for Normalizing Flows
normflows: A PyTorch Package for Normalizing FlowsJournal of Open Source Software (JOSS), 2023
Vincent Stimper
David Liu
Andrew Campbell
V. Berenz
Lukas Ryll
Bernhard Schölkopf
José Miguel Hernández-Lobato
AI4CE
252
82
0
26 Jan 2023
Solving Inverse Physics Problems with Score Matching
Solving Inverse Physics Problems with Score MatchingNeural Information Processing Systems (NeurIPS), 2023
Benjamin Holzschuh
S. Vegetti
Nils Thuerey
DiffM
205
14
0
24 Jan 2023
Counterfactual (Non-)identifiability of Learned Structural Causal Models
Counterfactual (Non-)identifiability of Learned Structural Causal Models
Arash Nasr-Esfahany
Emre Kıcıman
198
15
0
22 Jan 2023
Spatial Attention Kinetic Networks with E(n)-Equivariance
Spatial Attention Kinetic Networks with E(n)-EquivarianceInternational Conference on Learning Representations (ICLR), 2023
Yuanqing Wang
J. Chodera
202
21
0
21 Jan 2023
Towards Flexibility and Interpretability of Gaussian Process State-Space
  Model
Towards Flexibility and Interpretability of Gaussian Process State-Space Model
Zhidi Lin
Feng Yin
Juan Maroñas
393
7
0
21 Jan 2023
Mathematical analysis of singularities in the diffusion model under the
  submanifold assumption
Mathematical analysis of singularities in the diffusion model under the submanifold assumptionEast Asian Journal on Applied Mathematics (EAJAM), 2023
Yubin Lu
Zhongjian Wang
G. Bal
DiffM
307
15
0
19 Jan 2023
Laser: Latent Set Representations for 3D Generative Modeling
Laser: Latent Set Representations for 3D Generative Modeling
Pol Moreno
Adam R. Kosiorek
Heiko Strathmann
Daniel Zoran
Rosália G. Schneider
Bjorn Winckler
L. Markeeva
T. Weber
Danilo Jimenez Rezende
BDL3DVDRL
248
5
0
13 Jan 2023
Designing losses for data-free training of normalizing flows on
  Boltzmann distributions
Designing losses for data-free training of normalizing flows on Boltzmann distributions
Loris Felardos
Jérôme Hénin
Guillaume Charpiat
AI4CE
196
9
0
13 Jan 2023
A Comprehensive Review of Data-Driven Co-Speech Gesture Generation
A Comprehensive Review of Data-Driven Co-Speech Gesture Generation
Simbarashe Nyatsanga
Taras Kucherenko
Chaitanya Ahuja
G. Henter
Michael Neff
SLR
427
130
0
13 Jan 2023
Deep Injective Prior for Inverse Scattering
Deep Injective Prior for Inverse ScatteringIEEE Transactions on Antennas and Propagation (IEEE Trans. Antennas Propag.), 2023
AmirEhsan Khorashadizadeh
Vahid Khorashadi-Zadeh
Sepehr Eskandari
Guy A. E. Vandenbosch
Ivan Dokmanić
258
12
0
08 Jan 2023
L-HYDRA: Multi-Head Physics-Informed Neural Networks
L-HYDRA: Multi-Head Physics-Informed Neural Networks
Zongren Zou
George Karniadakis
AI4CE
157
32
0
05 Jan 2023
NODAGS-Flow: Nonlinear Cyclic Causal Structure Learning
NODAGS-Flow: Nonlinear Cyclic Causal Structure LearningInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Muralikrishnna G. Sethuraman
Romain Lopez
Ramkumar Veppathur Mohan
Faramarz Fekri
Tommaso Biancalani
Jan-Christian Hütter
CML
249
17
0
04 Jan 2023
End-to-End Modeling Hierarchical Time Series Using Autoregressive Transformer and Conditional Normalizing Flow based Reconciliation
End-to-End Modeling Hierarchical Time Series Using Autoregressive Transformer and Conditional Normalizing Flow based Reconciliation
Shiyu Wang
Fan Zhou
Yinbo Sun
Lintao Ma
James Y. Zhang
Yang Zheng
BDLAI4TS
181
9
0
28 Dec 2022
EndoBoost: a plug-and-play module for false positive suppression during
  computer-aided polyp detection in real-world colonoscopy (with dataset)
EndoBoost: a plug-and-play module for false positive suppression during computer-aided polyp detection in real-world colonoscopy (with dataset)
Haoran Wang
Yan Zhu
W. Qin
Yizhe Zhang
Pinghong Zhou
Quanlin Li
Shuo Wang
Zhijian Song
227
2
0
23 Dec 2022
Distribution-aware Goal Prediction and Conformant Model-based Planning
  for Safe Autonomous Driving
Distribution-aware Goal Prediction and Conformant Model-based Planning for Safe Autonomous Driving
Jonathan M Francis
Bingqing Chen
Weiran Yao
Eric Nyberg
Jean Oh
OOD
196
6
0
16 Dec 2022
Generative structured normalizing flow Gaussian processes applied to
  spectroscopic data
Generative structured normalizing flow Gaussian processes applied to spectroscopic data
Natalie Klein
N. Panda
P. Gasda
Diane Oyen
148
1
0
14 Dec 2022
DeeProb-kit: a Python Library for Deep Probabilistic Modelling
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Lorenzo Loconte
G. Gala
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168
3
0
08 Dec 2022
On the Robustness of Normalizing Flows for Inverse Problems in Imaging
On the Robustness of Normalizing Flows for Inverse Problems in ImagingIEEE International Conference on Computer Vision (ICCV), 2022
Seongmin Hong
I. Park
S. Chun
266
9
0
08 Dec 2022
Deep Variational Inverse Scattering
Deep Variational Inverse ScatteringEuropean Conference on Antennas and Propagation (EuCAP), 2022
AmirEhsan Khorashadizadeh
A. Aghababaei
Tin Vlavsić
Hieu Nguyen
Ivan Dokmanić
BDLUQCV
161
5
0
08 Dec 2022
Fast Point Cloud Generation with Straight Flows
Fast Point Cloud Generation with Straight FlowsComputer Vision and Pattern Recognition (CVPR), 2022
Lemeng Wu
Dilin Wang
Chengyue Gong
Xingchao Liu
Yunyang Xiong
Rakesh Ranjan
Raghuraman Krishnamoorthi
Vikas Chandra
Qiang Liu
275
58
0
04 Dec 2022
Towards Explainability in Modular Autonomous Vehicle Software
Towards Explainability in Modular Autonomous Vehicle Software
Hongrui Zheng
Zirui Zang
Shuo Yang
Rahul Mangharam
216
0
0
01 Dec 2022
Taming Hyperparameter Tuning in Continuous Normalizing Flows Using the
  JKO Scheme
Taming Hyperparameter Tuning in Continuous Normalizing Flows Using the JKO SchemeScientific Reports (Sci Rep), 2022
Alexander Vidal
Samy Wu Fung
Luis Tenorio
Stanley Osher
L. Nurbekyan
230
24
0
30 Nov 2022
Waveflow: Enforcing boundary conditions in smooth normalizing flows with
  application to fermionic wave functions
Waveflow: Enforcing boundary conditions in smooth normalizing flows with application to fermionic wave functionsAPL Machine Learning (AML), 2022
Luca Thiede
Chong Sun
A. Aspuru‐Guzik
270
2
0
27 Nov 2022
PaCMO: Partner Dependent Human Motion Generation in Dyadic Human
  Activity using Neural Operators
PaCMO: Partner Dependent Human Motion Generation in Dyadic Human Activity using Neural Operators
Md Ashiqur Rahman
Jasorsi Ghosh
Hrishikesh Viswanath
Kamyar Azizzadenesheli
Aniket Bera
195
9
0
25 Nov 2022
Sparse Probabilistic Circuits via Pruning and Growing
Sparse Probabilistic Circuits via Pruning and GrowingNeural Information Processing Systems (NeurIPS), 2022
Meihua Dang
Hoang Trung-Dung
Karen Ullrich
TPM
223
23
0
22 Nov 2022
Diffeomorphic Information Neural Estimation
Diffeomorphic Information Neural EstimationAAAI Conference on Artificial Intelligence (AAAI), 2022
Bao Duong
T. Nguyen
226
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20 Nov 2022
Validation Diagnostics for SBI algorithms based on Normalizing Flows
Validation Diagnostics for SBI algorithms based on Normalizing Flows
J. Linhart
Alexandre Gramfort
P. L. C. R. M. -. Inria
167
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17 Nov 2022
Normalizing Flows for Hierarchical Bayesian Analysis: A Gravitational
  Wave Population Study
Normalizing Flows for Hierarchical Bayesian Analysis: A Gravitational Wave Population Study
David Ruhe
Kaze W. K. Wong
M. Cranmer
Patrick Forré
272
9
0
15 Nov 2022
Diffusion Models for Medical Image Analysis: A Comprehensive Survey
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Amirhossein Kazerouni
Ehsan Khodapanah Aghdam
Moein Heidari
Reza Azad
Mohsen Fayyaz
Ilker Hacihaliloglu
Dorit Merhof
DiffMMedIm
510
577
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14 Nov 2022
Aspects of scaling and scalability for flow-based sampling of lattice
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Aspects of scaling and scalability for flow-based sampling of lattice QCDEuropean Physical Journal A (EPJ A), 2022
Ryan Abbott
M. S. Albergo
Aleksandar Botev
D. Boyda
Kyle Cranmer
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Ali Razavi
Danilo Jimenez Rezende
F. Romero-López
P. Shanahan
Julian M. Urban
270
43
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14 Nov 2022
OverFlow: Putting flows on top of neural transducers for better TTS
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Shivam Mehta
Ambika Kirkland
Harm Lameris
Jonas Beskow
Éva Székely
G. Henter
AI4TS
278
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Learning Riemannian Stable Dynamical Systems via Diffeomorphisms
Learning Riemannian Stable Dynamical Systems via DiffeomorphismsConference on Robot Learning (CoRL), 2022
Jiechao Zhang
Hadi Beik-Mohammadi
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Flows for Flows: Training Normalizing Flows Between Arbitrary
  Distributions with Maximum Likelihood Estimation
Flows for Flows: Training Normalizing Flows Between Arbitrary Distributions with Maximum Likelihood Estimation
Samuel Klein
C. Pollard
J. A. Raine
TPM
271
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An optimal control perspective on diffusion-based generative modeling
An optimal control perspective on diffusion-based generative modeling
Julius Berner
Lorenz Richter
Karen Ullrich
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460
133
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