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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
AltUB: Alternating Training Method to Update Base Distribution of
  Normalizing Flow for Anomaly Detection
AltUB: Alternating Training Method to Update Base Distribution of Normalizing Flow for Anomaly Detection
Yeongmin Kim
Huiwon Jang
Dongkeon Lee
Ho-Jin Choi
184
11
0
26 Oct 2022
Adaptive deep density approximation for fractional Fokker-Planck
  equations
Adaptive deep density approximation for fractional Fokker-Planck equationsJournal of Scientific Computing (J. Sci. Comput.), 2022
Li Zeng
Xiaoliang Wan
Tao Zhou
158
8
0
26 Oct 2022
CaloFlow for CaloChallenge Dataset 1
CaloFlow for CaloChallenge Dataset 1SciPost Physics (SciPost Phys.), 2022
Claudius Krause
Ian Pang
David Shih
AI4CE
225
30
0
25 Oct 2022
Whitening Convergence Rate of Coupling-based Normalizing Flows
Whitening Convergence Rate of Coupling-based Normalizing FlowsNeural Information Processing Systems (NeurIPS), 2022
Felix Dräxler
Christoph Schnörr
Ullrich Kothe
218
7
0
25 Oct 2022
Optimization for Amortized Inverse Problems
Optimization for Amortized Inverse ProblemsInternational Conference on Machine Learning (ICML), 2022
Tianci Liu
Tong Yang
Quan Zhang
Qi Lei
293
6
0
25 Oct 2022
Transport Reversible Jump Proposals
Transport Reversible Jump ProposalsInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2022
L. Davies
Roberto Salomone
Matthew Sutton
Christopher C. Drovandi
BDL
226
3
0
22 Oct 2022
Improved Normalizing Flow-Based Speech Enhancement using an All-pole
  Gammatone Filterbank for Conditional Input Representation
Improved Normalizing Flow-Based Speech Enhancement using an All-pole Gammatone Filterbank for Conditional Input RepresentationSpoken Language Technology Workshop (SLT), 2022
Martin Strauss
Matteo Torcoli
B. Edler
162
7
0
21 Oct 2022
TTTFlow: Unsupervised Test-Time Training with Normalizing Flow
TTTFlow: Unsupervised Test-Time Training with Normalizing FlowIEEE Workshop/Winter Conference on Applications of Computer Vision (WACV), 2022
David Osowiechi
G. A. V. Hakim
Mehrdad Noori
Milad Cheraghalikhani
Ismail Ben Ayed
Christian Desrosiers
OOD
193
35
0
20 Oct 2022
Sampling using Adaptive Regenerative Processes
Sampling using Adaptive Regenerative Processes
Hector McKimm
Andi Q. Wang
M. Pollock
Christian P. Robert
Gareth O. Roberts
197
1
0
18 Oct 2022
Transfer learning with affine model transformation
Transfer learning with affine model transformationNeural Information Processing Systems (NeurIPS), 2022
Shunya Minami
Kenji Fukumizu
Yoshihiro Hayashi
Ryo Yoshida
230
1
0
18 Oct 2022
Invertible Monotone Operators for Normalizing Flows
Invertible Monotone Operators for Normalizing FlowsNeural Information Processing Systems (NeurIPS), 2022
Byeongkeun Ahn
Chiyoon Kim
Youngjoon Hong
Hyunwoo J. Kim
TPM
242
10
0
15 Oct 2022
Blind Super-Resolution for Remote Sensing Images via Conditional
  Stochastic Normalizing Flows
Blind Super-Resolution for Remote Sensing Images via Conditional Stochastic Normalizing Flows
Hanlin Wu
Ning Ni
Shan Wang
Li-bao Zhang
145
8
0
14 Oct 2022
Latent Temporal Flows for Multivariate Analysis of Wearables Data
Latent Temporal Flows for Multivariate Analysis of Wearables DataMachine Learning in Health Care (MLHC), 2022
Magda Amiridi
Gregory Darnell
S. Jewell
AI4TS
191
2
0
14 Oct 2022
Learning Multivariate CDFs and Copulas using Tensor Factorization
Learning Multivariate CDFs and Copulas using Tensor Factorization
Magda Amiridi
N. Sidiropoulos
227
2
0
13 Oct 2022
Robust Neural Posterior Estimation and Statistical Model Criticism
Robust Neural Posterior Estimation and Statistical Model CriticismNeural Information Processing Systems (NeurIPS), 2022
Daniel Ward
Patrick W Cannon
Mark Beaumont
Matteo Fasiolo
Sebastian M. Schmon
232
54
0
12 Oct 2022
Modular Flows: Differential Molecular Generation
Modular Flows: Differential Molecular GenerationNeural Information Processing Systems (NeurIPS), 2022
Yogesh Verma
Samuel Kaski
Markus Heinonen
Vikas Garg
367
15
0
12 Oct 2022
Neural Importance Sampling for Rapid and Reliable Gravitational-Wave
  Inference
Neural Importance Sampling for Rapid and Reliable Gravitational-Wave InferencePhysical Review Letters (PRL), 2022
Maximilian Dax
Stephen R. Green
J. Gair
M. Purrer
J. Wildberger
Jakob H. Macke
A. Buonanno
Bernhard Schölkopf
BDL
217
78
0
11 Oct 2022
Contrastive Neural Ratio Estimation for Simulation-based Inference
Contrastive Neural Ratio Estimation for Simulation-based Inference
Benjamin Kurt Miller
Christoph Weniger
Patrick Forré
359
15
0
11 Oct 2022
Sequential Neural Score Estimation: Likelihood-Free Inference with
  Conditional Score Based Diffusion Models
Sequential Neural Score Estimation: Likelihood-Free Inference with Conditional Score Based Diffusion ModelsInternational Conference on Machine Learning (ICML), 2022
Louis Sharrock
J. Simons
Song Liu
Mark Beaumont
DiffM
296
52
0
10 Oct 2022
Design Amortization for Bayesian Optimal Experimental Design
Design Amortization for Bayesian Optimal Experimental DesignAAAI Conference on Artificial Intelligence (AAAI), 2022
Noble Kennamer
Steven Walton
Alexander Ihler
158
7
0
07 Oct 2022
Flow Matching for Generative Modeling
Flow Matching for Generative ModelingInternational Conference on Learning Representations (ICLR), 2022
Y. Lipman
Ricky T. Q. Chen
Heli Ben-Hamu
Maximilian Nickel
Matt Le
OOD
1.2K
3,095
0
06 Oct 2022
Connecting Surrogate Safety Measures to Crash Probablity via Causal
  Probabilistic Time Series Prediction
Connecting Surrogate Safety Measures to Crash Probablity via Causal Probabilistic Time Series Prediction
Jiajian Lu
Offer Grembek
M. Hansen
AI4TS
103
0
0
04 Oct 2022
Cooperation in the Latent Space: The Benefits of Adding Mixture
  Components in Variational Autoencoders
Cooperation in the Latent Space: The Benefits of Adding Mixture Components in Variational AutoencodersInternational Conference on Machine Learning (ICML), 2022
Oskar Kviman
Ricky Molén
A. Hotti
Semih Kurt
Victor Elvira
J. Lagergren
322
15
0
30 Sep 2022
Training Normalizing Flows from Dependent Data
Training Normalizing Flows from Dependent DataInternational Conference on Machine Learning (ICML), 2022
Matthias Kirchler
Christoph Lippert
Matthias Kirchler
TPM
220
2
0
29 Sep 2022
ButterflyFlow: Building Invertible Layers with Butterfly Matrices
ButterflyFlow: Building Invertible Layers with Butterfly MatricesInternational Conference on Machine Learning (ICML), 2022
Chenlin Meng
Linqi Zhou
Kristy Choi
Tri Dao
Stefano Ermon
TPM
308
13
0
28 Sep 2022
Local_INN: Implicit Map Representation and Localization with Invertible
  Neural Networks
Local_INN: Implicit Map Representation and Localization with Invertible Neural NetworksIEEE International Conference on Robotics and Automation (ICRA), 2022
Zirui Zang
Hongrui Zheng
Johannes Betz
Rahul Mangharam
162
8
0
24 Sep 2022
Turning Normalizing Flows into Monge Maps with Geodesic Gaussian
  Preserving Flows
Turning Normalizing Flows into Monge Maps with Geodesic Gaussian Preserving Flows
G. Morel
Lucas Drumetz
Simon Benaïchouche
Nicolas Courty
F. Rousseau
OT
427
6
0
22 Sep 2022
Adaptive Multi-stage Density Ratio Estimation for Learning Latent Space
  Energy-based Model
Adaptive Multi-stage Density Ratio Estimation for Learning Latent Space Energy-based ModelNeural Information Processing Systems (NeurIPS), 2022
Zhisheng Xiao
Tian Han
217
21
0
19 Sep 2022
Sample-based Uncertainty Quantification with a Single Deterministic
  Neural Network
Sample-based Uncertainty Quantification with a Single Deterministic Neural NetworkInternational Joint Conference on Computational Intelligence (IJCCI), 2022
T. Kanazawa
Chetan Gupta
UQCV
238
6
0
17 Sep 2022
Asymptotic Statistical Analysis of $f$-divergence GAN
Asymptotic Statistical Analysis of fff-divergence GAN
Xinwei Shen
Kani Chen
Tong Zhang
238
2
0
14 Sep 2022
Deep Variational Free Energy Approach to Dense Hydrogen
Deep Variational Free Energy Approach to Dense HydrogenPhysical Review Letters (PRL), 2022
H.-j. Xie
Ziqun Li
Han Wang
Linfeng Zhang
Lei Wang
228
14
0
13 Sep 2022
Flow Straight and Fast: Learning to Generate and Transfer Data with
  Rectified Flow
Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified FlowInternational Conference on Learning Representations (ICLR), 2022
Xingchao Liu
Chengyue Gong
Qiang Liu
OOD
1.1K
2,128
0
07 Sep 2022
A Survey on Generative Diffusion Model
A Survey on Generative Diffusion ModelIEEE Transactions on Knowledge and Data Engineering (TKDE), 2022
Hanqun Cao
Cheng Tan
Zhangyang Gao
Yilun Xu
Guangyong Chen
Pheng-Ann Heng
Stan Z. Li
MedIm
815
434
0
06 Sep 2022
Bayesian Neural Network Inference via Implicit Models and the Posterior
  Predictive Distribution
Bayesian Neural Network Inference via Implicit Models and the Posterior Predictive Distribution
J. Dabrowski
D. Pagendam
UQCVBDL
146
0
0
06 Sep 2022
Investigating the Impact of Model Misspecification in Neural
  Simulation-based Inference
Investigating the Impact of Model Misspecification in Neural Simulation-based Inference
Patrick W Cannon
Daniel Ward
Sebastian M. Schmon
233
45
0
05 Sep 2022
Conditional Independence Testing via Latent Representation Learning
Conditional Independence Testing via Latent Representation LearningIndustrial Conference on Data Mining (IDM), 2022
Bao Duong
T. Nguyen
BDLCML
210
8
0
04 Sep 2022
Diffusion Models: A Comprehensive Survey of Methods and Applications
Diffusion Models: A Comprehensive Survey of Methods and ApplicationsACM Computing Surveys (ACM CSUR), 2022
Ling Yang
Zhilong Zhang
Yingxia Shao
Shenda Hong
Runsheng Xu
Yue Zhao
Wentao Zhang
Tengjiao Wang
Ming-Hsuan Yang
DiffMMedIm
1.6K
1,949
0
02 Sep 2022
Positive Difference Distribution for Image Outlier Detection using
  Normalizing Flows and Contrastive Data
Positive Difference Distribution for Image Outlier Detection using Normalizing Flows and Contrastive Data
R. Schmier
Ullrich Kothe
C. Straehle
178
7
0
30 Aug 2022
Tackling Multimodal Device Distributions in Inverse Photonic Design
  using Invertible Neural Networks
Tackling Multimodal Device Distributions in Inverse Photonic Design using Invertible Neural Networks
Michel Frising
J. Bravo-Abad
F. Prins
180
6
0
29 Aug 2022
Uncovering dark matter density profiles in dwarf galaxies with graph
  neural networks
Uncovering dark matter density profiles in dwarf galaxies with graph neural networks
Tri Nguyen
S. Mishra-Sharma
R. Williams
L. Necib
152
5
0
26 Aug 2022
Deep Structural Causal Shape Models
Deep Structural Causal Shape Models
Rajat Rasal
Daniel Coelho De Castro
Nick Pawlowski
Ben Glocker
3DVMedIm
247
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23 Aug 2022
Neural PCA for Flow-Based Representation Learning
Neural PCA for Flow-Based Representation LearningInternational Joint Conference on Artificial Intelligence (IJCAI), 2022
Shen Li
Bryan Hooi
DRL
169
1
0
23 Aug 2022
Function Classes for Identifiable Nonlinear Independent Component
  Analysis
Function Classes for Identifiable Nonlinear Independent Component AnalysisNeural Information Processing Systems (NeurIPS), 2022
Simon Buchholz
M. Besserve
Bernhard Schölkopf
200
48
0
12 Aug 2022
A biology-driven deep generative model for cell-type annotation in
  cytometry
A biology-driven deep generative model for cell-type annotation in cytometry
Quentin Blampey
N. Bercovici
C. Dutertre
I. Pic
F. André
J. M. Ribeiro
P. Cournède
111
5
0
11 Aug 2022
HSIC-InfoGAN: Learning Unsupervised Disentangled Representations by
  Maximising Approximated Mutual Information
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Xiao Liu
Spyridon Thermos
Pedro Sanchez
Alison Q. OÑeil
Sotirios A. Tsaftaris
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Interpretable Uncertainty Quantification in AI for HEP
Interpretable Uncertainty Quantification in AI for HEP
Thomas Y. Chen
B. Dey
A. Ghosh
Michael Kagan
Brian D. Nord
Nesar Ramachandra
214
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Graph neural networks for materials science and chemistry
Graph neural networks for materials science and chemistryCommunications Materials (Commun. Mater.), 2022
Patrick Reiser
Marlen Neubert
André Eberhard
Luca Torresi
Chen Zhou
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Houssam Metni
Clint van Hoesel
Henrik Schopmans
T. Sommer
Pascal Friederich
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379
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An Optimal Likelihood Free Method for Biological Model Selection
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Flow Annealed Importance Sampling Bootstrap
Flow Annealed Importance Sampling BootstrapInternational Conference on Learning Representations (ICLR), 2022
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Vincent Stimper
G. Simm
Bernhard Schölkopf
José Miguel Hernández-Lobato
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Exploring Generative Neural Temporal Point Process
Exploring Generative Neural Temporal Point Process
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Lirong Wu
Guojiang Zhao
Pai Liu
Stan Z. Li
DiffM
265
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0
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