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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
On the Asymptotic Mean Square Error Optimality of Diffusion Models
On the Asymptotic Mean Square Error Optimality of Diffusion Models
B. Fesl
Benedikt Bock
Florian Strasser
Michael Baur
M. Joham
Wolfgang Utschick
DiffM
441
9
0
05 Mar 2024
Normalizing Flow-based Differentiable Particle Filters
Normalizing Flow-based Differentiable Particle Filters
Xiongjie Chen
Yunpeng Li
218
0
0
03 Mar 2024
Approximations to the Fisher Information Metric of Deep Generative
  Models for Out-Of-Distribution Detection
Approximations to the Fisher Information Metric of Deep Generative Models for Out-Of-Distribution Detection
Sam Dauncey
Chris Holmes
Christopher Williams
Fabian Falck
372
1
0
03 Mar 2024
Towards Generalizable Tumor Synthesis
Towards Generalizable Tumor Synthesis
Qi Chen
Xiaoxi Chen
Haorui Song
Zhiwei Xiong
Yaoyao Liu
Chen Wei
Zongwei Zhou
MedIm
308
70
0
29 Feb 2024
Sequential transport maps using SoS density estimation and
  $α$-divergences
Sequential transport maps using SoS density estimation and ααα-divergences
Benjamin Zanger
Tiangang Cui
Martin Schreiber
O. Zahm
205
1
0
27 Feb 2024
DeepDRK: Deep Dependency Regularized Knockoff for Feature Selection
DeepDRK: Deep Dependency Regularized Knockoff for Feature Selection
Hongyu Shen
Yici Yan
Zhizhen Zhao
220
0
0
27 Feb 2024
Stable Training of Normalizing Flows for High-dimensional Variational
  Inference
Stable Training of Normalizing Flows for High-dimensional Variational Inference
Daniel Andrade
BDLTPM
224
5
0
26 Feb 2024
Generative AI in Vision: A Survey on Models, Metrics and Applications
Generative AI in Vision: A Survey on Models, Metrics and Applications
Gaurav Raut
Apoorv Singh
VLMMedIm
242
13
0
26 Feb 2024
Fine-Tuning of Continuous-Time Diffusion Models as Entropy-Regularized
  Control
Fine-Tuning of Continuous-Time Diffusion Models as Entropy-Regularized Control
Masatoshi Uehara
Yulai Zhao
Kevin Black
Ehsan Hajiramezanali
Gabriele Scalia
N. Diamant
Alex Tseng
Tommaso Biancalani
Sergey Levine
280
85
0
23 Feb 2024
Learning Exceptional Subgroups by End-to-End Maximizing KL-divergence
Learning Exceptional Subgroups by End-to-End Maximizing KL-divergence
Sascha Xu
Nils Philipp Walter
Janis Kalofolias
Jilles Vreeken
148
5
0
20 Feb 2024
MGF: Mixed Gaussian Flow for Diverse Trajectory Prediction
MGF: Mixed Gaussian Flow for Diverse Trajectory Prediction
Jiahe Chen
Jinkun Cao
Dahua Lin
Kris Kitani
Jiangmiao Pang
229
10
0
19 Feb 2024
Mapping the Ethics of Generative AI: A Comprehensive Scoping Review
Mapping the Ethics of Generative AI: A Comprehensive Scoping Review
Thilo Hagendorff
263
84
0
13 Feb 2024
Diffeomorphic Measure Matching with Kernels for Generative Modeling
Diffeomorphic Measure Matching with Kernels for Generative Modeling
Biraj Pandey
Bamdad Hosseini
Pau Batlle
H. Owhadi
231
4
0
12 Feb 2024
Generative Modeling of Discrete Joint Distributions by E-Geodesic Flow
  Matching on Assignment Manifolds
Generative Modeling of Discrete Joint Distributions by E-Geodesic Flow Matching on Assignment Manifolds
Bastian Boll
Daniel Gonzalez-Alvarado
Christoph Schnörr
DRL
235
4
0
12 Feb 2024
Score-based Diffusion Models via Stochastic Differential Equations -- a Technical Tutorial
Score-based Diffusion Models via Stochastic Differential Equations -- a Technical TutorialStatistics Survey (Stat. Surv.), 2024
Wenpin Tang
Hanyang Zhao
DiffM
397
43
0
12 Feb 2024
Probabilistic Forecasting of Irregular Time Series via Conditional Flows
Probabilistic Forecasting of Irregular Time Series via Conditional Flows
Vijaya Krishna Yalavarthi
Randolf Scholz
Stefan Born
Lars Schmidt-Thieme
AI4TS
363
1
0
09 Feb 2024
Iterated Denoising Energy Matching for Sampling from Boltzmann Densities
Iterated Denoising Energy Matching for Sampling from Boltzmann Densities
Tara Akhound-Sadegh
Jarrid Rector-Brooks
A. Bose
Sarthak Mittal
Pablo Lemos
...
Siamak Ravanbakhsh
Gauthier Gidel
Yoshua Bengio
Nikolay Malkin
Alexander Tong
DiffM
279
91
0
09 Feb 2024
Implicit Diffusion: Efficient Optimization through Stochastic Sampling
Implicit Diffusion: Efficient Optimization through Stochastic Sampling
Pierre Marion
Anna Korba
Peter Bartlett
Mathieu Blondel
Valentin De Bortoli
Arnaud Doucet
Felipe Llinares-López
Courtney Paquette
Quentin Berthet
437
19
0
08 Feb 2024
DySLIM: Dynamics Stable Learning by Invariant Measure for Chaotic
  Systems
DySLIM: Dynamics Stable Learning by Invariant Measure for Chaotic Systems
Yair Schiff
Zhong Yi Wan
Jeffrey B. Parker
Stephan Hoyer
Volodymyr Kuleshov
Fei Sha
Leonardo Zepeda-Núñez
417
20
0
06 Feb 2024
PQMass: Probabilistic Assessment of the Quality of Generative Models using Probability Mass Estimation
PQMass: Probabilistic Assessment of the Quality of Generative Models using Probability Mass EstimationInternational Conference on Learning Representations (ICLR), 2024
Pablo Lemos
Sammy N. Sharief
Nikolay Malkin
Salma Salhi
Connor Stone
Laurence Perreault Levasseur
Y. Hezaveh
516
7
0
06 Feb 2024
Monotone, Bi-Lipschitz, and Polyak-Lojasiewicz Networks
Monotone, Bi-Lipschitz, and Polyak-Lojasiewicz Networks
Ruigang Wang
Krishnamurthy Dvijotham
I. Manchester
415
9
0
02 Feb 2024
IN-Flow: Instance Normalization Flow for Non-stationary Time Series Forecasting
IN-Flow: Instance Normalization Flow for Non-stationary Time Series Forecasting
Wei Fan
Shun Zheng
Pengyang Wang
Rui Xie
Kun Yi
Yanjie Fu
Jiang Bian
Yanjie Fu
AI4TSOOD
166
2
0
30 Jan 2024
Active learning of Boltzmann samplers and potential energies with
  quantum mechanical accuracy
Active learning of Boltzmann samplers and potential energies with quantum mechanical accuracy
Ana Molina-Taborda
Pilar Cossio
O. Lopez-Acevedo
Marylou Gabrié
241
6
0
29 Jan 2024
AdvNF: Reducing Mode Collapse in Conditional Normalising Flows using
  Adversarial Learning
AdvNF: Reducing Mode Collapse in Conditional Normalising Flows using Adversarial LearningSciPost Physics (SciPost Phys.), 2024
V. Kanaujia
Mathias S. Scheurer
Vipul Arora
GANDRL
232
4
0
29 Jan 2024
Graph-accelerated Markov Chain Monte Carlo using Approximate Samples
Graph-accelerated Markov Chain Monte Carlo using Approximate Samples
Leo L. Duan
Anirban Bhattacharya
244
1
0
25 Jan 2024
Interplay between depth and width for interpolation in neural ODEs
Interplay between depth and width for interpolation in neural ODEs
Antonio Álvarez-López
Arselane Hadj Slimane
Enrique Zuazua
353
14
0
18 Jan 2024
Tractable Optimal Experimental Design using Transport Maps
Tractable Optimal Experimental Design using Transport MapsInverse Problems (IP), 2024
Karina Koval
Roland Herzog
Robert Scheichl
OT
309
10
0
15 Jan 2024
Deep Learning With DAGs
Deep Learning With DAGsSocial Science Research Network (SSRN), 2024
Sourabh Vivek Balgi
Adel Daoud
Jose M. Pena
G. Wodtke
Jesse Zhou
AI4CECML
263
5
0
12 Jan 2024
Combining Normalizing Flows and Quasi-Monte Carlo
Combining Normalizing Flows and Quasi-Monte Carlo
Charly Andral
BDL
149
2
0
11 Jan 2024
Sampling in Unit Time with Kernel Fisher-Rao Flow
Sampling in Unit Time with Kernel Fisher-Rao FlowInternational Conference on Machine Learning (ICML), 2024
A. Maurais
Youssef Marzouk
302
24
0
08 Jan 2024
Simulation-Based Inference with Quantile Regression
Simulation-Based Inference with Quantile Regression
He Jia
222
4
0
04 Jan 2024
Transformer Neural Autoregressive Flows
Transformer Neural Autoregressive Flows
Massimiliano Patacchiola
Aliaksandra Shysheya
Katja Hofmann
Richard Turner
TPM
219
7
0
03 Jan 2024
Diffusion Models, Image Super-Resolution And Everything: A Survey
Diffusion Models, Image Super-Resolution And Everything: A SurveyIEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2024
Brian B. Moser
Arundhati S. Shanbhag
Federico Raue
Stanislav Frolov
Sebastián M. Palacio
Andreas Dengel
479
102
0
01 Jan 2024
Channelling Multimodality Through a Unimodalizing Transport: Warp-U
  Sampler and Stochastic Bridge Sampling
Channelling Multimodality Through a Unimodalizing Transport: Warp-U Sampler and Stochastic Bridge Sampling
Fei Ding
David E. Jones
Shiyuan He
Xiao-Li Meng
OT
166
0
0
01 Jan 2024
Time-changed normalizing flows for accurate SDE modeling
Time-changed normalizing flows for accurate SDE modeling
Naoufal El Bekri
Lucas Drumetz
Franck Vermet
AI4TSBDL
293
0
0
22 Dec 2023
Curated LLM: Synergy of LLMs and Data Curation for tabular augmentation
  in low-data regimes
Curated LLM: Synergy of LLMs and Data Curation for tabular augmentation in low-data regimes
Nabeel Seedat
Nicolas Huynh
B. V. Breugel
M. Schaar
346
49
0
19 Dec 2023
Dirichlet-based Uncertainty Quantification for Personalized Federated
  Learning with Improved Posterior Networks
Dirichlet-based Uncertainty Quantification for Personalized Federated Learning with Improved Posterior Networks
Nikita Kotelevskii
Samuel Horváth
Karthik Nandakumar
Martin Takáč
Maxim Panov
UQCVFedMLOOD
188
13
0
18 Dec 2023
NM-FlowGAN: Modeling sRGB Noise with a Hybrid Approach based on
  Normalizing Flows and Generative Adversarial Networks
NM-FlowGAN: Modeling sRGB Noise with a Hybrid Approach based on Normalizing Flows and Generative Adversarial Networks
Young Joo Han
Ha-Jin Yu
214
1
0
15 Dec 2023
A Compact and Semantic Latent Space for Disentangled and Controllable
  Image Editing
A Compact and Semantic Latent Space for Disentangled and Controllable Image EditingConference on Visual Media Production (CVMP), 2023
Gwilherm Lesné
Y. Gousseau
Saïd Ladjal
A. Newson
DRL
99
0
0
13 Dec 2023
TERM Model: Tensor Ring Mixture Model for Density Estimation
TERM Model: Tensor Ring Mixture Model for Density Estimation
Ruituo Wu
Jiani Liu
Ce Zhu
Anh-Huy Phan
Ivan Oseledets
Yipeng Liu
219
2
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13 Dec 2023
Exploring Plain ViT Reconstruction for Multi-class Unsupervised Anomaly
  Detection
Exploring Plain ViT Reconstruction for Multi-class Unsupervised Anomaly Detection
Jiangning Zhang
Xuhai Chen
Yabiao Wang
Chengjie Wang
Yong Liu
Xiangtai Li
Ming-Hsuan Yang
Dacheng Tao
281
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0
12 Dec 2023
Optimizing Likelihood-free Inference using Self-supervised Neural
  Symmetry Embeddings
Optimizing Likelihood-free Inference using Self-supervised Neural Symmetry Embeddings
D. Chatterjee
Philip C. Harris
Maanas Goel
Malina Desai
Michael W. Coughlin
E. Katsavounidis
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11 Dec 2023
Consistency Models for Scalable and Fast Simulation-Based Inference
Consistency Models for Scalable and Fast Simulation-Based InferenceNeural Information Processing Systems (NeurIPS), 2023
Marvin Schmitt
Valentin Pratz
Ullrich Kothe
Paul-Christian Bürkner
Stefan T. Radev
347
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09 Dec 2023
MVDD: Multi-View Depth Diffusion Models
MVDD: Multi-View Depth Diffusion ModelsEuropean Conference on Computer Vision (ECCV), 2023
Zhen Wang
Qiangeng Xu
Feitong Tan
Menglei Chai
Shichen Liu
Rohit Pandey
S. Fanello
A. Kadambi
Yinda Zhang
DiffM
263
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0
08 Dec 2023
Application of machine learning technique for a fast forecast of
  aggregation kinetics in space-inhomogeneous systems
Application of machine learning technique for a fast forecast of aggregation kinetics in space-inhomogeneous systems
M. A. Larchenko
R. R. Zagidullin
V. V. Palyulin
N. Brilliantov
AI4TS
65
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Enhancing Polynomial Chaos Expansion Based Surrogate Modeling using a
  Novel Probabilistic Transfer Learning Strategy
Enhancing Polynomial Chaos Expansion Based Surrogate Modeling using a Novel Probabilistic Transfer Learning Strategy
Wyatt Bridgman
Uma Balakrishnan
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119
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Multimodal Industrial Anomaly Detection by Crossmodal Feature Mapping
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Simulation-Based Inference of Surface Accumulation and Basal Melt Rates
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