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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
Koopman operator learning using invertible neural networks
Koopman operator learning using invertible neural networks
Yuhuang Meng
Jian-Kai Huang
Yue Qiu
262
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BayesFlow: Amortized Bayesian Workflows With Neural Networks
BayesFlow: Amortized Bayesian Workflows With Neural NetworksJournal of Open Source Software (JOSS), 2023
Stefan T. Radev
Marvin Schmitt
Lukas Schumacher
Lasse Elsemüller
Valentin Pratz
Yannik Schalte
Ullrich Kothe
Paul-Christian Bürkner
BDL
359
44
0
28 Jun 2023
Stochastic Gradient Bayesian Optimal Experimental Designs for
  Simulation-based Inference
Stochastic Gradient Bayesian Optimal Experimental Designs for Simulation-based Inference
Vincent D. Zaballa
E. Hui
204
2
0
27 Jun 2023
On the Usefulness of Synthetic Tabular Data Generation
On the Usefulness of Synthetic Tabular Data Generation
Dionysis Manousakas
Sergul Aydore
190
15
0
27 Jun 2023
Deep Normalizing Flows for State Estimation
Deep Normalizing Flows for State EstimationFusion (Fusion), 2023
Harrison Delecki
Liam A. Kruse
Marc R. Schlichting
Mykel J. Kochenderfer
138
3
0
27 Jun 2023
Equivariant flow matching
Equivariant flow matchingNeural Information Processing Systems (NeurIPS), 2023
Leon Klein
Andreas Krämer
Frank Noé
295
116
0
26 Jun 2023
eCat: An End-to-End Model for Multi-Speaker TTS & Many-to-Many
  Fine-Grained Prosody Transfer
eCat: An End-to-End Model for Multi-Speaker TTS & Many-to-Many Fine-Grained Prosody TransferInterspeech (Interspeech), 2023
Ammar Abbas
S. Karlapati
Bastian Schnell
Penny Karanasou
M. G. Moya
Amith Nagaraj
Ayman Boustati
Nicole Peinelt
Alexis Moinet
Thomas Drugman
276
3
0
20 Jun 2023
Variational Sequential Optimal Experimental Design using Reinforcement
  Learning
Variational Sequential Optimal Experimental Design using Reinforcement LearningComputer Methods in Applied Mechanics and Engineering (CMAME), 2023
Wanggang Shen
Jiayuan Dong
Xun Huan
176
12
0
17 Jun 2023
A Heavy-Tailed Algebra for Probabilistic Programming
A Heavy-Tailed Algebra for Probabilistic ProgrammingNeural Information Processing Systems (NeurIPS), 2023
Feynman T. Liang
Liam Hodgkinson
Michael W. Mahoney
249
3
0
15 Jun 2023
On Certified Generalization in Structured Prediction
On Certified Generalization in Structured PredictionNeural Information Processing Systems (NeurIPS), 2023
Bastian Boll
Christoph Schnörr
276
0
0
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Conditional Matrix Flows for Gaussian Graphical Models
Conditional Matrix Flows for Gaussian Graphical ModelsNeural Information Processing Systems (NeurIPS), 2023
M. Negri
F. A. Torres
Volker Roth
171
5
0
12 Jun 2023
Explaining Predictive Uncertainty with Information Theoretic Shapley
  Values
Explaining Predictive Uncertainty with Information Theoretic Shapley ValuesNeural Information Processing Systems (NeurIPS), 2023
David S. Watson
Joshua O'Hara
Niek Tax
Richard Mudd
Ido Guy
TDIFAtt
281
38
0
09 Jun 2023
Causal normalizing flows: from theory to practice
Causal normalizing flows: from theory to practiceNeural Information Processing Systems (NeurIPS), 2023
Adrián Javaloy
Pablo Sánchez-Martín
Isabel Valera
TPMCMLAI4CE
401
37
0
08 Jun 2023
Bayesian model calibration for diblock copolymer thin film self-assembly
  using power spectrum of microscopy data and machine learning surrogate
Bayesian model calibration for diblock copolymer thin film self-assembly using power spectrum of microscopy data and machine learning surrogateComputer Methods in Applied Mechanics and Engineering (CMAME), 2023
Lianghao Cao
Keyi Wu
J. Oden
P. Chen
Omar Ghattas
211
3
0
08 Jun 2023
L-C2ST: Local Diagnostics for Posterior Approximations in
  Simulation-Based Inference
L-C2ST: Local Diagnostics for Posterior Approximations in Simulation-Based InferenceNeural Information Processing Systems (NeurIPS), 2023
J. Linhart
Alexandre Gramfort
Pedro L. C. Rodrigues
340
17
0
06 Jun 2023
Enhanced Distribution Modelling via Augmented Architectures For Neural
  ODE Flows
Enhanced Distribution Modelling via Augmented Architectures For Neural ODE Flows
Etrit Haxholli
Marco Lorenzi
98
0
0
05 Jun 2023
Faster Training of Diffusion Models and Improved Density Estimation via
  Parallel Score Matching
Faster Training of Diffusion Models and Improved Density Estimation via Parallel Score Matching
Etrit Haxholli
Marco Lorenzi
DiffM
80
3
0
05 Jun 2023
Correcting Auto-Differentiation in Neural-ODE Training
Correcting Auto-Differentiation in Neural-ODE Training
Yewei Xu
Shi Chen
Qin Li
269
1
0
03 Jun 2023
A Conditional Normalizing Flow for Accelerated Multi-Coil MR Imaging
A Conditional Normalizing Flow for Accelerated Multi-Coil MR ImagingInternational Conference on Machine Learning (ICML), 2023
Jeffrey Wen
Rizwan Ahmad
Philip Schniter
MedIm
202
11
0
02 Jun 2023
Learning Causally Disentangled Representations via the Principle of
  Independent Causal Mechanisms
Learning Causally Disentangled Representations via the Principle of Independent Causal MechanismsInternational Joint Conference on Artificial Intelligence (IJCAI), 2023
Aneesh Komanduri
Yongkai Wu
Feng Chen
Xintao Wu
CMLOOD
488
18
0
02 Jun 2023
Insights into Closed-form IPM-GAN Discriminator Guidance for Diffusion Modeling
Insights into Closed-form IPM-GAN Discriminator Guidance for Diffusion Modeling
Aadithya Srikanth
Siddarth Asokan
Nishanth Shetty
C. Seelamantula
308
0
0
02 Jun 2023
Balanced Training of Energy-Based Models with Adaptive Flow Sampling
Balanced Training of Energy-Based Models with Adaptive Flow Sampling
Louis Grenioux
Eric Moulines
Marylou Gabrié
353
5
0
01 Jun 2023
Nonparametric Identifiability of Causal Representations from Unknown
  Interventions
Nonparametric Identifiability of Causal Representations from Unknown InterventionsNeural Information Processing Systems (NeurIPS), 2023
Julius von Kügelgen
M. Besserve
Wendong Liang
Luigi Gresele
Armin Kekić
Elias Bareinboim
David M. Blei
Bernhard Schölkopf
CML
527
80
0
01 Jun 2023
DiffLoad: Uncertainty Quantification in Load Forecasting with Diffusion
  Model
DiffLoad: Uncertainty Quantification in Load Forecasting with Diffusion ModelIEEE Transactions on Power Systems (IEEE Trans. Power Syst.), 2023
Zhixian Wang
Qingsong Wen
Chaoli Zhang
Liang Sun
Yi Wang
DiffM
311
6
0
31 May 2023
Efficient Training of Energy-Based Models Using Jarzynski Equality
Efficient Training of Energy-Based Models Using Jarzynski EqualityNeural Information Processing Systems (NeurIPS), 2023
D. Carbone
Mengjian Hua
Simon Coste
Eric Vanden-Eijnden
288
16
0
30 May 2023
One-Line-of-Code Data Mollification Improves Optimization of
  Likelihood-based Generative Models
One-Line-of-Code Data Mollification Improves Optimization of Likelihood-based Generative ModelsNeural Information Processing Systems (NeurIPS), 2023
Ba-Hien Tran
Giulio Franzese
Pietro Michiardi
Maurizio Filippone
DiffM
412
4
0
30 May 2023
Perturbation-Assisted Sample Synthesis: A Novel Approach for Uncertainty
  Quantification
Perturbation-Assisted Sample Synthesis: A Novel Approach for Uncertainty Quantification
Yifei Liu
Rex Shen
Xiaotong Shen
DiffM
332
1
0
30 May 2023
GC-Flow: A Graph-Based Flow Network for Effective Clustering
GC-Flow: A Graph-Based Flow Network for Effective ClusteringInternational Conference on Machine Learning (ICML), 2023
Tianchun Wang
F. Mirzazadeh
Xinming Zhang
Jing Chen
BDL
216
9
0
26 May 2023
Causal Component Analysis
Causal Component AnalysisNeural Information Processing Systems (NeurIPS), 2023
Wendong Liang
Armin Kekić
Julius von Kügelgen
Simon Buchholz
M. Besserve
Luigi Gresele
Bernhard Schölkopf
CML
408
50
0
26 May 2023
Functional Flow Matching
Functional Flow MatchingInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Gavin Kerrigan
Giosue Migliorini
Padhraic Smyth
380
34
0
26 May 2023
Flow Matching for Scalable Simulation-Based Inference
Flow Matching for Scalable Simulation-Based InferenceNeural Information Processing Systems (NeurIPS), 2023
Maximilian Dax
J. Wildberger
Simon Buchholz
Stephen R. Green
Jakob H. Macke
Bernhard Schölkopf
178
98
0
26 May 2023
Kernel Density Matrices for Probabilistic Deep Learning
Kernel Density Matrices for Probabilistic Deep LearningQuantum Machine Intelligence (QMI), 2023
Fabio A. González
Raúl Ramos-Pollán
Joseph A. Gallego-Mejia
171
5
0
26 May 2023
Lagrangian Flow Networks for Conservation Laws
Lagrangian Flow Networks for Conservation LawsInternational Conference on Learning Representations (ICLR), 2023
F. A. Torres
M. Negri
M. Inversi
Jonathan Aellen
Volker Roth
243
4
0
26 May 2023
Parameter Estimation in DAGs from Incomplete Data via Optimal Transport
Parameter Estimation in DAGs from Incomplete Data via Optimal TransportInternational Conference on Machine Learning (ICML), 2023
Vy Vo
Trung Le
L. Vuong
He Zhao
Edwin V. Bonilla
Dinh Q. Phung
OT
310
4
0
25 May 2023
Deep Stochastic Processes via Functional Markov Transition Operators
Deep Stochastic Processes via Functional Markov Transition OperatorsNeural Information Processing Systems (NeurIPS), 2023
Jin Xu
Emilien Dupont
Kaspar Martens
Tom Rainforth
Yee Whye Teh
258
6
0
24 May 2023
Training Energy-Based Normalizing Flow with Score-Matching Objectives
Training Energy-Based Normalizing Flow with Score-Matching ObjectivesNeural Information Processing Systems (NeurIPS), 2023
Chen-Hao Chao
Wei-Fang Sun
Yen-Chang Hsu
Z. Kira
Chun-Yi Lee
296
7
0
24 May 2023
Simultaneous identification of models and parameters of scientific
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Simultaneous identification of models and parameters of scientific simulatorsInternational Conference on Machine Learning (ICML), 2023
Cornelius Schroder
Jakob H. Macke
294
7
0
24 May 2023
Wasserstein Gaussianization and Efficient Variational Bayes for Robust
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Wasserstein Gaussianization and Efficient Variational Bayes for Robust Bayesian Synthetic LikelihoodJournal of Computational And Graphical Statistics (JCGS), 2023
Nhat-Minh Nguyen
Minh-Ngoc Tran
Christopher C. Drovandi
David J. Nott
180
1
0
24 May 2023
Discriminative calibration: Check Bayesian computation from simulations
  and flexible classifier
Discriminative calibration: Check Bayesian computation from simulations and flexible classifierNeural Information Processing Systems (NeurIPS), 2023
Yuling Yao
Justin Domke
UQLM
471
2
0
24 May 2023
Squared Neural Families: A New Class of Tractable Density Models
Squared Neural Families: A New Class of Tractable Density ModelsNeural Information Processing Systems (NeurIPS), 2023
Russell Tsuchida
Cheng Soon Ong
Dino Sejdinovic
TPM
243
14
0
22 May 2023
On Learning the Tail Quantiles of Driving Behavior Distributions via
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Jia Yu Tee
Oliver De Candido
Wolfgang Utschick
Philipp Geiger
249
1
0
22 May 2023
Normalizing flow sampling with Langevin dynamics in the latent space
Normalizing flow sampling with Langevin dynamics in the latent spaceMachine-mediated learning (ML), 2023
Florentin Coeurdoux
N. Dobigeon
P. Chainais
DRL
163
9
0
20 May 2023
Inductive Simulation of Calorimeter Showers with Normalizing Flows
Inductive Simulation of Calorimeter Showers with Normalizing Flows
M. Buckley
Claudius Krause
Ian Pang
David Shih
AI4CE
297
37
0
19 May 2023
Computing high-dimensional optimal transport by flow neural networks
Computing high-dimensional optimal transport by flow neural networksInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Chen Xu
Xiuyuan Cheng
Yao Xie
OT
627
7
0
19 May 2023
Estimation Beyond Data Reweighting: Kernel Method of Moments
Estimation Beyond Data Reweighting: Kernel Method of MomentsInternational Conference on Machine Learning (ICML), 2023
Heiner Kremer
Yassine Nemmour
Bernhard Schölkopf
Jia-Jie Zhu
299
7
0
18 May 2023
BlindHarmony: "Blind" Harmonization for MR Images via Flow model
BlindHarmony: "Blind" Harmonization for MR Images via Flow modelIEEE International Conference on Computer Vision (ICCV), 2023
Hwihun Jeong
Heejoon Byun
Dong un Kang
Jongho Lee
MedIm
236
8
0
18 May 2023
Score Operator Newton transport
Score Operator Newton transportInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023
N. Chandramoorthy
F. Schaefer
Youssef Marzouk
OT
341
1
0
16 May 2023
To smooth a cloud or to pin it down: Guarantees and Insights on Score
  Matching in Denoising Diffusion Models
To smooth a cloud or to pin it down: Guarantees and Insights on Score Matching in Denoising Diffusion Models
Francisco Vargas
Teodora Reu
A. Kerekes
Michael M Bronstein
DiffM
368
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0
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Out-of-Distribution Detection for Adaptive Computer Vision
Out-of-Distribution Detection for Adaptive Computer VisionScandinavian Conference on Image Analysis (SCIA), 2023
S. Lind
Rudolph Triebel
Luigi Nardi
V. Krüger
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135
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MolHF: A Hierarchical Normalizing Flow for Molecular Graph Generation
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Yiheng Zhu
Zhenqiu Ouyang
Ben Liao
Jialun Wu
YiXuan Wu
Chang-Yu Hsieh
Tingjun Hou
Jian Wu
AI4CE
269
11
0
15 May 2023
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