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Variational Inference with Normalizing Flows
v1v2v3v4v5v6 (latest)

Variational Inference with Normalizing Flows

21 May 2015
Danilo Jimenez Rezende
S. Mohamed
    DRLBDL
ArXiv (abs)PDFHTML

Papers citing "Variational Inference with Normalizing Flows"

50 / 2,268 papers shown
Title
Deep generative models as the probability transformation functions
Deep generative models as the probability transformation functions
Vitalii Bondar
Vira Babenko
Roman Trembovetskyi
Yurii Korobeinyk
Viktoriya Dzyuba
22
0
0
20 Jun 2025
A Variational Framework for Improving Naturalness in Generative Spoken Language Models
A Variational Framework for Improving Naturalness in Generative Spoken Language Models
Li-Wei Chen
Takuya Higuchi
Zakaria Aldeneh
Ahmed Hussen Abdelaziz
Alexander I. Rudnicky
29
0
0
17 Jun 2025
Polyra Swarms: A Shape-Based Approach to Machine Learning
Polyra Swarms: A Shape-Based Approach to Machine Learning
Simon Klüttermann
Emmanuel Müller
17
0
0
16 Jun 2025
ErrorEraser: Unlearning Data Bias for Improved Continual Learning
ErrorEraser: Unlearning Data Bias for Improved Continual Learning
Xuemei Cao
Hanlin Gu
Xin Yang
Bingjun Wei
Haoyang Liang
Xiangkun Wang
Tianrui Li
CLLKELMMU
71
0
0
11 Jun 2025
Inherited or produced? Inferring protein production kinetics when protein counts are shaped by a cell's division history
Inherited or produced? Inferring protein production kinetics when protein counts are shaped by a cell's division history
Pedro Pessoa
Juan Andres Martinez
Vincent Vandenbroucke
Frank Delvigne
Steve Pressé
63
0
0
11 Jun 2025
Variational Inference Optimized Using the Curved Geometry of Coupled Free Energy
Variational Inference Optimized Using the Curved Geometry of Coupled Free Energy
Kenric Nelson
Igor Oliveira
Amenah Al-Najafi
Fode Zhang
Hon Keung Tony Ng
DRL
32
0
0
10 Jun 2025
AstroCompress: A benchmark dataset for multi-purpose compression of astronomical data
Tuan Truong
Rithwik Sudharsan
Yibo Yang
Peter Xiangyuan Ma
Ruihan Yang
Stephan Mandt
Joshua S. Bloom
38
0
0
10 Jun 2025
Variational Supervised Contrastive Learning
Variational Supervised Contrastive Learning
Ziwen Wang
Jiajun Fan
Thao Nguyen
Heng Ji
Ge Liu
DRLSSL
47
0
0
09 Jun 2025
Self-Cascaded Diffusion Models for Arbitrary-Scale Image Super-Resolution
Self-Cascaded Diffusion Models for Arbitrary-Scale Image Super-Resolution
Junseo Bang
Joonhee Lee
Kyeonghyun Lee
Haechang Lee
Dong un Kang
Se Young Chun
17
0
0
09 Jun 2025
Continuous Semi-Implicit Models
Continuous Semi-Implicit Models
L. Yu
Jiajun Zha
Tong Yang
Tianyu Xie
Xiangyu Zhang
S.-H. Gary Chan
Cheng Zhang
DiffM
15
0
0
07 Jun 2025
Multilevel neural simulation-based inference
Multilevel neural simulation-based inference
Yuga Hikida
Ayush Bharti
Niall Jeffrey
F. Briol
62
0
0
06 Jun 2025
STARFlow: Scaling Latent Normalizing Flows for High-resolution Image Synthesis
STARFlow: Scaling Latent Normalizing Flows for High-resolution Image Synthesis
Jiatao Gu
Tianrong Chen
David Berthelot
Huangjie Zheng
Yuyang Wang
Ruixiang Zhang
Laurent Dinh
Miguel Angel Bautista
Josh Susskind
Shuangfei Zhai
45
0
0
06 Jun 2025
Learning normalized image densities via dual score matching
Florentin Guth
Zahra Kadkhodaie
Eero P. Simoncelli
DiffM
106
0
0
05 Jun 2025
Semi-Implicit Variational Inference via Kernelized Path Gradient Descent
Tobias Pielok
Bernd Bischl
David Rügamer
114
0
0
05 Jun 2025
On Fitting Flow Models with Large Sinkhorn Couplings
On Fitting Flow Models with Large Sinkhorn Couplings
Michal Klein
Alireza Mousavi-Hosseini
Stephen Zhang
Marco Cuturi
39
0
0
05 Jun 2025
Amortized variational transdimensional inference
Laurence Davies
Dan Mackinlay
Rafael Oliveira
Scott A. Sisson
DRLBDL
123
0
0
05 Jun 2025
Revisiting Unbiased Implicit Variational Inference
Revisiting Unbiased Implicit Variational Inference
Tobias Pielok
Bernd Bischl
David Rügamer
BDL
90
0
0
04 Jun 2025
Temporal Causal-based Simulation for Realistic Time-series Generation
Temporal Causal-based Simulation for Realistic Time-series Generation
Nikolaos Gkorgkolis
Nikolaos Kougioulis
Mingxue Wang
Bora Caglayan
Andrea Tonon
Dario Simionato
Ioannis Tsamardinos
CML
31
0
0
02 Jun 2025
Asymptotically exact variational flows via involutive MCMC kernels
Asymptotically exact variational flows via involutive MCMC kernels
Zuheng Xu
Trevor Campbell
36
0
0
02 Jun 2025
Beyond Diagonal Covariance: Flexible Posterior VAEs via Free-Form Injective Flows
Beyond Diagonal Covariance: Flexible Posterior VAEs via Free-Form Injective Flows
Peter Sorrenson
Lukas Lührs
Hans Olischläger
Ullrich Kothe
72
0
0
02 Jun 2025
PseudoVC: Improving One-shot Voice Conversion with Pseudo Paired Data
PseudoVC: Improving One-shot Voice Conversion with Pseudo Paired Data
Songjun Cao
Qinghua Wu
Jie Chen
Jin Li
Long Ma
40
0
0
01 Jun 2025
FORT: Forward-Only Regression Training of Normalizing Flows
FORT: Forward-Only Regression Training of Normalizing Flows
Danyal Rehman
Oscar Davis
Jiarui Lu
Jian Tang
M. Bronstein
Yoshua Bengio
Alexander Tong
A. Bose
OOD
40
0
0
01 Jun 2025
Generator Based Inference (GBI)
Generator Based Inference (GBI)
Chi Lung Cheng
Ranit Das
Runze Li
R. Mastandrea
Vinicius Mikuni
Benjamin Nachman
David Shih
Gup Singh
27
0
0
30 May 2025
BIMA: Bijective Maximum Likelihood Learning Approach to Hallucination Prediction and Mitigation in Large Vision-Language Models
BIMA: Bijective Maximum Likelihood Learning Approach to Hallucination Prediction and Mitigation in Large Vision-Language Models
Huu-Thien Tran
Thanh-Dat Truong
Khoa Luu
MLLM
18
0
0
30 May 2025
DiCoFlex: Model-agnostic diverse counterfactuals with flexible control
DiCoFlex: Model-agnostic diverse counterfactuals with flexible control
Oleksii Furman
Ulvi Movsum-zada
Patryk Marszalek
Maciej Ziȩba
Marek Śmieja
BDL
30
0
0
29 May 2025
Normalizing Flows are Capable Models for RL
Normalizing Flows are Capable Models for RL
Raj Ghugare
Benjamin Eysenbach
OffRLAI4CE
86
0
0
29 May 2025
Symplectic Generative Networks (SGNs): A Hamiltonian Framework for Invertible Deep Generative Modeling
Symplectic Generative Networks (SGNs): A Hamiltonian Framework for Invertible Deep Generative Modeling
Agnideep Aich
Ashit Aich
Bruce Wade
14
0
0
28 May 2025
Wavelet Flow For Extragalactic Foreground Simulations
Wavelet Flow For Extragalactic Foreground Simulations
M. Mebratu
W. L. K. Wu
21
0
0
27 May 2025
Importance Weighted Score Matching for Diffusion Samplers with Enhanced Mode Coverage
Importance Weighted Score Matching for Diffusion Samplers with Enhanced Mode Coverage
Chenguang Wang
Xiaoyu Zhang
Kaiyuan Cui
Weichen Zhao
Yongtao Guan
Tianshu Yu
DiffM
102
0
0
26 May 2025
Discrete Markov Bridge
Discrete Markov Bridge
Hengli Li
Yuxuan Wang
Song-Chun Zhu
Ying Nian Wu
Zilong Zheng
DiffM
69
0
0
26 May 2025
FlashMD: long-stride, universal prediction of molecular dynamics
FlashMD: long-stride, universal prediction of molecular dynamics
Filippo Bigi
Sanggyu Chong
Agustinus Kristiadi
Michele Ceriotti
AI4CE
72
1
0
25 May 2025
Smoothie: Smoothing Diffusion on Token Embeddings for Text Generation
Smoothie: Smoothing Diffusion on Token Embeddings for Text Generation
Alexander Shabalin
Viacheslav Meshchaninov
Dmitry Vetrov
44
0
0
24 May 2025
Follow the Energy, Find the Path: Riemannian Metrics from Energy-Based Models
Follow the Energy, Find the Path: Riemannian Metrics from Energy-Based Models
Louis Bethune
David Vigouroux
Yilun Du
Rufin VanRullen
Thomas Serre
Victor Boutin
DiffM
75
0
0
23 May 2025
Learning Flexible Forward Trajectories for Masked Molecular Diffusion
Learning Flexible Forward Trajectories for Masked Molecular Diffusion
Hyunjin Seo
Taewon Kim
Sihyun Yu
SungSoo Ahn
DiffMAI4CE
172
0
0
22 May 2025
Multivariate Latent Recalibration for Conditional Normalizing Flows
Multivariate Latent Recalibration for Conditional Normalizing Flows
Victor Dheur
Souhaib Ben Taieb
BDL
161
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0
22 May 2025
Generative AI for Autonomous Driving: A Review
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Katharina Winter
Abhishek Vivekanandan
Rupert Polley
Yinzhe Shen
Christian Schlauch
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Christian Wirth
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Nadja Klein
Fabian B. Flohr
Hanno Gottschalk
94
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Last Layer Empirical Bayes
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Valentin Villecroze
Yixin Wang
Gabriel Loaiza-Ganem
UQCVBDL
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CacheFlow: Fast Human Motion Prediction by Cached Normalizing Flow
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Takahiro Maeda
Jinkun Cao
Norimichi Ukita
Kris Kitani
3DH
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Multi-View Wireless Sensing via Conditional Generative Learning: Framework and Model Design
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Ziqing Xing
Zhaoyang Zhang
Zirui Chen
Hongning Ruan
Zhaohui Yang
DiffM3DV
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Mean Flows for One-step Generative Modeling
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Zhengyang Geng
Mingyang Deng
Xingjian Bai
J. Zico Kolter
Kaiming He
DiffM
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Proximal optimal transport divergences
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Ricardo Baptista
Panagiota Birmpa
Markos A. Katsoulakis
Luc Rey-Bellet
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OT
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Supervised Models Can Generalize Also When Trained on Random Labels
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Thomas B. Schön
OODSSL
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Generative Models in Computational Pathology: A Comprehensive Survey on Methods, Applications, and Challenges
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Xinfeng Zhang
Xiaoming Qi Xinyu Wu
Feng Chen
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Huazhu Fu
MedImLM&MAAI4CE
163
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Missing Data Imputation by Reducing Mutual Information with Rectified Flows
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Jiahao Yu
Qizhen Ying
Leyang Wang
Z. L. Jiang
Song Liu
69
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Sejun Park
Ganguk Hwang
FedML
108
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Path Gradients after Flow Matching
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Lorenz Vaitl
Leon Klein
51
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FlowVAT: Normalizing Flow Variational Inference with Affine-Invariant Tempering
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Shixiao Liang
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TPM
86
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ConDiSim: Conditional Diffusion Models for Simulation Based Inference
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Andreas Hellander
Prashant Singh
DiffM
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MiniMax-Speech: Intrinsic Zero-Shot Text-to-Speech with a Learnable Speaker Encoder
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Congchao Guo
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Yiying Zhou
Yize Zhang
Yuan Lu
Yucen He
66
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