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Variational Inference with Normalizing Flows

Variational Inference with Normalizing Flows

21 May 2015
Danilo Jimenez Rezende
S. Mohamed
    DRL
    BDL
ArXivPDFHTML

Papers citing "Variational Inference with Normalizing Flows"

50 / 900 papers shown
Title
Supervised Models Can Generalize Also When Trained on Random Labels
Supervised Models Can Generalize Also When Trained on Random Labels
Oskar Allerbo
Thomas B. Schön
OOD
SSL
29
0
0
16 May 2025
Deep Latent Variable Model based Vertical Federated Learning with Flexible Alignment and Labeling Scenarios
Deep Latent Variable Model based Vertical Federated Learning with Flexible Alignment and Labeling Scenarios
Kihun Hong
Sejun Park
Ganguk Hwang
FedML
35
0
0
16 May 2025
Generative Models in Computational Pathology: A Comprehensive Survey on Methods, Applications, and Challenges
Generative Models in Computational Pathology: A Comprehensive Survey on Methods, Applications, and Challenges
Yuan Zhang
Xinfeng Zhang
Xiaoming Qi Xinyu Wu
Feng Chen
Guanyu Yang
Huazhu Fu
MedIm
LM&MA
AI4CE
31
0
0
16 May 2025
Missing Data Imputation by Reducing Mutual Information with Rectified Flows
Missing Data Imputation by Reducing Mutual Information with Rectified Flows
Jiahao Yu
Qizhen Ying
Leyang Wang
Z. L. Jiang
Song Liu
2
0
0
16 May 2025
Path Gradients after Flow Matching
Path Gradients after Flow Matching
Lorenz Vaitl
Leon Klein
19
0
0
15 May 2025
FlowVAT: Normalizing Flow Variational Inference with Affine-Invariant Tempering
FlowVAT: Normalizing Flow Variational Inference with Affine-Invariant Tempering
Juehang Qin
Shixiao Liang
C. Tunnell
TPM
39
0
0
15 May 2025
Recent Advances in Medical Imaging Segmentation: A Survey
Recent Advances in Medical Imaging Segmentation: A Survey
Fares Bougourzi
Abdenour Hadid
OOD
44
0
0
14 May 2025
ConDiSim: Conditional Diffusion Models for Simulation Based Inference
ConDiSim: Conditional Diffusion Models for Simulation Based Inference
Mayank Nautiyal
A. Hellander
Prashant Singh
DiffM
32
0
0
13 May 2025
Compression, Regularity, Randomness and Emergent Structure: Rethinking Physical Complexity in the Data-Driven Era
Compression, Regularity, Randomness and Emergent Structure: Rethinking Physical Complexity in the Data-Driven Era
Nima Dehghani
AI4CE
32
0
0
12 May 2025
MiniMax-Speech: Intrinsic Zero-Shot Text-to-Speech with a Learnable Speaker Encoder
MiniMax-Speech: Intrinsic Zero-Shot Text-to-Speech with a Learnable Speaker Encoder
Bowen Zhang
Congchao Guo
Geng Yang
Hang Yu
Haozhe Zhang
...
Yichen Xiao
Yiying Zhou
Yujie Zhang
Yuan Lu
Yucen He
26
0
0
12 May 2025
MAGE:A Multi-stage Avatar Generator with Sparse Observations
MAGE:A Multi-stage Avatar Generator with Sparse Observations
Fangyu Du
Yang Yang
Xuehao Gao
Hongye Hou
VGen
28
0
0
09 May 2025
Generating Reliable Synthetic Clinical Trial Data: The Role of Hyperparameter Optimization and Domain Constraints
Generating Reliable Synthetic Clinical Trial Data: The Role of Hyperparameter Optimization and Domain Constraints
Waldemar Hahn
Jan-Niklas Eckardt
Christoph Röllig
Martin Sedlmayr
J. Middeke
M. Wolfien
42
0
0
08 May 2025
Boosting Statistic Learning with Synthetic Data from Pretrained Large Models
Boosting Statistic Learning with Synthetic Data from Pretrained Large Models
Jialong Jiang
Wenkang Hu
Jian Huang
Yuling Jiao
Xu Liu
DiffM
50
0
0
08 May 2025
Conformal Prediction with Corrupted Labels: Uncertain Imputation and Robust Re-weighting
Conformal Prediction with Corrupted Labels: Uncertain Imputation and Robust Re-weighting
Shai Feldman
Stephen Bates
Yaniv Romano
34
0
0
07 May 2025
Hamiltonian Normalizing Flows as kinetic PDE solvers: application to the 1D Vlasov-Poisson Equations
Hamiltonian Normalizing Flows as kinetic PDE solvers: application to the 1D Vlasov-Poisson Equations
Vincent Souveton
Sébastien Terrana
41
0
0
07 May 2025
Real-Time Person Image Synthesis Using a Flow Matching Model
Real-Time Person Image Synthesis Using a Flow Matching Model
Jiwoo Jeong
Kirok Kim
Wooju Kim
Nam-Joon Kim
3DH
81
0
0
06 May 2025
Physics-Informed Sylvester Normalizing Flows for Bayesian Inference in Magnetic Resonance Spectroscopy
Physics-Informed Sylvester Normalizing Flows for Bayesian Inference in Magnetic Resonance Spectroscopy
Julian P Merkofer
D. V. D. Sande
A. Bhogal
Ruud J. G. van Sloun
32
0
0
06 May 2025
Learning and Transferring Physical Models through Derivatives
Learning and Transferring Physical Models through Derivatives
Alessandro Trenta
Andrea Cossu
Davide Bacciu
AI4CE
43
0
0
02 May 2025
Distilling Two-Timed Flow Models by Separately Matching Initial and Terminal Velocities
Distilling Two-Timed Flow Models by Separately Matching Initial and Terminal Velocities
Pramook Khungurn
Pratch Piyawongwisal
Sira Sriswadi
Supasorn Suwajanakorn
37
0
0
02 May 2025
What's Wrong with Your Synthetic Tabular Data? Using Explainable AI to Evaluate Generative Models
What's Wrong with Your Synthetic Tabular Data? Using Explainable AI to Evaluate Generative Models
Jan Kapar
Niklas Koenen
Martin Jullum
66
0
0
29 Apr 2025
Model uncertainty quantification using feature confidence sets for outcome excursions
Model uncertainty quantification using feature confidence sets for outcome excursions
Junting Ren
Armin Schwartzman
64
0
0
28 Apr 2025
Score-Debiased Kernel Density Estimation
Score-Debiased Kernel Density Estimation
Elliot L. Epstein
Rajat Dwaraknath
Thanawat Sornwanee
John Winnicki
Jerry Weihong Liu
17
0
0
27 Apr 2025
Likelihood-Free Variational Autoencoders
Likelihood-Free Variational Autoencoders
Chen Xu
Qiang Wang
Lijun Sun
DiffM
DRL
88
0
0
24 Apr 2025
Statistical Guarantees in Synthetic Data through Conformal Adversarial Generation
Statistical Guarantees in Synthetic Data through Conformal Adversarial Generation
Rahul Vishwakarma
Shrey Dharmendra Modi
Vishwanath Seshagiri
83
0
0
23 Apr 2025
Latent Bayesian Optimization via Autoregressive Normalizing Flows
Latent Bayesian Optimization via Autoregressive Normalizing Flows
Seunghun Lee
Jinyoung Park
Jaewon Chu
Minseo Yoon
H. Kim
BDL
45
2
0
21 Apr 2025
Spectral Dictionary Learning for Generative Image Modeling
Spectral Dictionary Learning for Generative Image Modeling
Andrew Kiruluta
DiffM
83
1
0
21 Apr 2025
Adjoint Sampling: Highly Scalable Diffusion Samplers via Adjoint Matching
Adjoint Sampling: Highly Scalable Diffusion Samplers via Adjoint Matching
Aaron J. Havens
Benjamin Kurt Miller
Bing Yan
Carles Domingo-Enrich
Anuroop Sriram
...
Brandon Amos
Brian Karrer
Xiang Fu
Guan-Horng Liu
Ricky T. Q. Chen
DiffM
55
0
0
16 Apr 2025
Improving the evaluation of samplers on multi-modal targets
Improving the evaluation of samplers on multi-modal targets
Louis Grenioux
Maxence Noble
Marylou Gabrié
182
0
0
11 Apr 2025
Gaussian Mixture Flow Matching Models
Gaussian Mixture Flow Matching Models
Hansheng Chen
Kai Zhang
Hao Tan
Zexiang Xu
Fujun Luan
Leonidas J. Guibas
Gordon Wetzstein
Sai Bi
DiffM
63
0
0
07 Apr 2025
ORAL: Prompting Your Large-Scale LoRAs via Conditional Recurrent Diffusion
ORAL: Prompting Your Large-Scale LoRAs via Conditional Recurrent Diffusion
Rana Muhammad Shahroz Khan
Dongwen Tang
Pingzhi Li
Kai Wang
Tianlong Chen
AI4CE
208
0
0
31 Mar 2025
ARFlow: Human Action-Reaction Flow Matching with Physical Guidance
ARFlow: Human Action-Reaction Flow Matching with Physical Guidance
Wentao Jiang
Jingya Wang
Haotao Lu
Kaiyang Ji
Baoxiong Jia
Siyuan Huang
Ye-ling Shi
49
0
0
21 Mar 2025
Multilevel Generative Samplers for Investigating Critical Phenomena
Ankur Singha
E. Cellini
K. Nicoli
K. Jansen
Stefan Kühn
Shinichi Nakajima
64
1
0
11 Mar 2025
Ideas in Inference-time Scaling can Benefit Generative Pre-training Algorithms
Jiaming Song
Linqi Zhou
DiffM
71
0
0
10 Mar 2025
Generative Artificial Intelligence in Robotic Manipulation: A Survey
Kun Zhang
Peng Yun
Jun Cen
Junhao Cai
DiDi Zhu
...
Qifeng Chen
Jia Pan
Wei Zhang
Bo Yang
Hua Chen
59
1
0
05 Mar 2025
A Dual-Purpose Framework for Backdoor Defense and Backdoor Amplification in Diffusion Models
A Dual-Purpose Framework for Backdoor Defense and Backdoor Amplification in Diffusion Models
Vu Tuan Truong Long
Bao Le
DiffM
AAML
270
0
0
26 Feb 2025
Bayesian Computation in Deep Learning
Bayesian Computation in Deep Learning
Wenlong Chen
Bolian Li
Ruqi Zhang
Yingzhen Li
BDL
75
0
0
25 Feb 2025
Towards Hierarchical Rectified Flow
Towards Hierarchical Rectified Flow
Yichi Zhang
Yici Yan
A. Schwing
Zhizhen Zhao
62
1
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24 Feb 2025
Accurate Forgetting for Heterogeneous Federated Continual Learning
Accurate Forgetting for Heterogeneous Federated Continual Learning
Abudukelimu Wuerkaixi
Sen Cui
J.N. Zhang
Kunda Yan
Bo Han
Gang Niu
Lei Fang
Changshui Zhang
Masashi Sugiyama
119
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Maximum Entropy Reinforcement Learning with Diffusion Policy
Maximum Entropy Reinforcement Learning with Diffusion Policy
Xiaoyi Dong
Jian Cheng
Xinsong Zhang
51
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Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes
Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes
Krithika S. Iyer
Mokshagna Sai Teja Karanam
Shireen Y. Elhabian
64
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An inpainting approach to manipulate asymmetry in pre-operative breast images
An inpainting approach to manipulate asymmetry in pre-operative breast images
Helena Montenegro
M. Cardoso
J. Cardoso
MedIm
49
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0
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Distribution Transformers: Fast Approximate Bayesian Inference With On-The-Fly Prior Adaptation
Distribution Transformers: Fast Approximate Bayesian Inference With On-The-Fly Prior Adaptation
George Whittle
Juliusz Ziomek
Jacob Rawling
Michael A. Osborne
97
2
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Trustworthy Evaluation of Generative AI Models
Trustworthy Evaluation of Generative AI Models
Zijun Gao
Yan Sun
112
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31 Jan 2025
One Model to Forecast Them All and in Entity Distributions Bind Them
Kutay Bölat
Simon Tindemans
AI4TS
58
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0
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CGI: Identifying Conditional Generative Models with Example Images
CGI: Identifying Conditional Generative Models with Example Images
Zhi-Hua Zhou
Hao-Zhe Tan
Peng-Xiao Song
Lan-Zhe Guo
DiffM
44
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0
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Bayesian Adaptive Calibration and Optimal Design
Bayesian Adaptive Calibration and Optimal Design
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Dino Sejdinovic
David Howard
Edwin Bonilla
113
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Conditional Diffusion Model for Electrical Impedance Tomography
Conditional Diffusion Model for Electrical Impedance Tomography
Duanpeng Shi
Wendong Zheng
Di Guo
Huaping Liu
DiffM
MedIm
225
2
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Bridge the Inference Gaps of Neural Processes via Expectation Maximization
Bridge the Inference Gaps of Neural Processes via Expectation Maximization
Q. Wang
Marco Federici
H. V. Hoof
UQCV
BDL
48
13
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Inflationary Flows: Calibrated Bayesian Inference with Diffusion-Based Models
Inflationary Flows: Calibrated Bayesian Inference with Diffusion-Based Models
Daniela de Albuquerque
John Pearson
DiffM
69
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BODex: Scalable and Efficient Robotic Dexterous Grasp Synthesis Using Bilevel Optimization
BODex: Scalable and Efficient Robotic Dexterous Grasp Synthesis Using Bilevel Optimization
Jiayi Chen
Yubin Ke
H. Wang
94
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