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Variational Inference: A Review for Statisticians
v1v2v3v4v5v6v7v8v9 (latest)

Variational Inference: A Review for Statisticians

4 January 2016
David M. Blei
A. Kucukelbir
Jon D. McAuliffe
    BDL
ArXiv (abs)PDFHTML

Papers citing "Variational Inference: A Review for Statisticians"

50 / 1,838 papers shown
Title
Locally Orderless Images for Optimization in Differentiable Rendering
Locally Orderless Images for Optimization in Differentiable Rendering
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Manmohan Chandraker
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Evaluating Negative Sampling Approaches for Neural Topic Models
Evaluating Negative Sampling Approaches for Neural Topic Models
Suman Adhya
Avishek Lahiri
Debarshi Kumar Sanyal
Partha Pratim Das
BDL
228
0
0
23 Mar 2025
FisherTune: Fisher-Guided Robust Tuning of Vision Foundation Models for Domain Generalized Segmentation
FisherTune: Fisher-Guided Robust Tuning of Vision Foundation Models for Domain Generalized Segmentation
Dong Zhao
Jinlong Li
Shuang Wang
Mengyao Wu
Qi Zang
N. Sebe
Zhun Zhong
465
1
0
23 Mar 2025
Quantification of Uncertainties in Probabilistic Deep Neural Network by Implementing Boosting of Variational Inference
Quantification of Uncertainties in Probabilistic Deep Neural Network by Implementing Boosting of Variational Inference
Pavia Bera
Sanjukta Bhanja
UQCVBDL
120
0
0
18 Mar 2025
Uncertainty Quantification for Data-Driven Machine Learning Models in Nuclear Engineering Applications: Where We Are and What Do We Need?
Uncertainty Quantification for Data-Driven Machine Learning Models in Nuclear Engineering Applications: Where We Are and What Do We Need?
Xu Wu
L. Moloko
P. Bokov
Gregory K. Delipei
Joshua Kaizer
K. Ivanov
AI4CE
71
0
0
16 Mar 2025
Massively Parallel Expectation Maximization For Approximate Posteriors
Thomas Heap
Sam Bowyer
Laurence Aitchison
69
0
0
11 Mar 2025
Vairiational Stochastic Games
Zhiyu Zhao
Haifeng Zhang
92
0
0
08 Mar 2025
Mixed Likelihood Variational Gaussian Processes
Kaiwen Wu
Craig Sanders
Benjamin Letham
Phillip Guan
109
0
0
06 Mar 2025
Parameter Expanded Stochastic Gradient Markov Chain Monte Carlo
Hyunsu Kim
G. Nam
Chulhee Yun
Hongseok Yang
Juho Lee
BDLUQCV
105
0
0
02 Mar 2025
End-To-End Learning of Gaussian Mixture Priors for Diffusion Sampler
Denis Blessing
Xiaogang Jia
Gerhard Neumann
DiffM
105
1
0
01 Mar 2025
Bayesian Active Learning for Multi-Criteria Comparative Judgement in Educational Assessment
Bayesian Active Learning for Multi-Criteria Comparative Judgement in Educational Assessment
Andy Gray
Alma A. M. Rahat
Tom Crick
Stephen Lindsay
ELM
91
1
0
01 Mar 2025
Variational Bayesian Pseudo-Coreset
Variational Bayesian Pseudo-Coreset
Hyungi Lee
Seanie Lee
Juho Lee
BDL
73
0
0
28 Feb 2025
Training Robust Graph Neural Networks by Modeling Noise Dependencies
Training Robust Graph Neural Networks by Modeling Noise Dependencies
Yeonjun In
Kanghoon Yoon
Sukwon Yun
Kibum Kim
Sungchul Kim
Chanyoung Park
OODNoLa
123
0
0
27 Feb 2025
Transfer Learning in Latent Contextual Bandits with Covariate Shift Through Causal Transportability
Transfer Learning in Latent Contextual Bandits with Covariate Shift Through Causal Transportability
Mingwei Deng
Ville Kyrki
Dominik Baumann
130
1
0
27 Feb 2025
Actively Inferring Optimal Measurement Sequences
Actively Inferring Optimal Measurement Sequences
Catherine F. Higham
Paul Henderson
R. Murray-Smith
DRL
134
0
0
25 Feb 2025
Federated Variational Inference for Bayesian Mixture Models
Federated Variational Inference for Bayesian Mixture Models
Jackie Rao
Francesca L. Crowe
Tom Marshall
S. Richardson
Paul D. W. Kirk
FedML
162
0
0
18 Feb 2025
In-Context Parametric Inference: Point or Distribution Estimators?
In-Context Parametric Inference: Point or Distribution Estimators?
Sarthak Mittal
Yoshua Bengio
Nikolay Malkin
Guillaume Lajoie
130
0
0
17 Feb 2025
Properties of Wasserstein Gradient Flows for the Sliced-Wasserstein Distance
Properties of Wasserstein Gradient Flows for the Sliced-Wasserstein Distance
Christophe Vauthier
Quentin Mérigot
Anna Korba
69
0
0
10 Feb 2025
Amortized In-Context Bayesian Posterior Estimation
Sarthak Mittal
Niels Leif Bracher
Guillaume Lajoie
P. Jaini
Marcus A. Brubaker
114
2
0
10 Feb 2025
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
210
4
0
04 Feb 2025
A Revisit of Total Correlation in Disentangled Variational Auto-Encoder with Partial Disentanglement
A Revisit of Total Correlation in Disentangled Variational Auto-Encoder with Partial Disentanglement
Chengrui Li
Yunmiao Wang
Yule Wang
Weihan Li
Dieter Jaeger
Anqi Wu
CoGeDRL
134
1
0
04 Feb 2025
Learning Hyperparameters via a Data-Emphasized Variational Objective
Learning Hyperparameters via a Data-Emphasized Variational Objective
Ethan Harvey
Mikhail Petrov
Michael C. Hughes
120
0
0
03 Feb 2025
Latent Thought Models with Variational Bayes Inference-Time Computation
Latent Thought Models with Variational Bayes Inference-Time Computation
Deqian Kong
Minglu Zhao
Dehong Xu
Bo Pang
Shu Wang
...
Zhangzhang Si
Chuan Li
Jianwen Xie
Sirui Xie
Ying Nian Wu
VLMLRMBDL
145
10
0
03 Feb 2025
HuViDPO:Enhancing Video Generation through Direct Preference Optimization for Human-Centric Alignment
HuViDPO:Enhancing Video Generation through Direct Preference Optimization for Human-Centric Alignment
Lifan Jiang
Boxi Wu
Jiahui Zhang
Xiaotong Guan
Shuang Chen
VGen
95
1
0
02 Feb 2025
Hellinger-Kantorovich Gradient Flows: Global Exponential Decay of Entropy Functionals
Hellinger-Kantorovich Gradient Flows: Global Exponential Decay of Entropy Functionals
Alexander Mielke
Jia Jie Zhu
172
2
0
28 Jan 2025
Learning the Regularization Strength for Deep Fine-Tuning via a Data-Emphasized Variational Objective
Learning the Regularization Strength for Deep Fine-Tuning via a Data-Emphasized Variational Objective
Ethan Harvey
Mikhail Petrov
Michael C. Hughes
162
0
0
28 Jan 2025
Bayesian Spatial Predictive Synthesis
Bayesian Spatial Predictive Synthesis
D. Cabel
S. Sugasawa
Masahiro Kato
K. Takanashi
K. McAlinn
155
4
0
28 Jan 2025
Robust and highly scalable estimation of directional couplings from time-shifted signals
Robust and highly scalable estimation of directional couplings from time-shifted signals
Luca Ambrogioni
Louis Rouillard
Demian Wassermann
172
0
0
28 Jan 2025
Information-theoretic Bayesian Optimization: Survey and Tutorial
Information-theoretic Bayesian Optimization: Survey and Tutorial
Eduardo C. Garrido-Merchán
154
1
0
22 Jan 2025
Globally Convergent Variational Inference
Globally Convergent Variational Inference
Declan McNamara
J. Loper
Jeffrey Regier
101
0
0
14 Jan 2025
Computational and Statistical Asymptotic Analysis of the JKO Scheme for Iterative Algorithms to update distributions
Computational and Statistical Asymptotic Analysis of the JKO Scheme for Iterative Algorithms to update distributions
Shang Wu
Yazhen Wang
104
0
0
11 Jan 2025
Analog Bayesian neural networks are insensitive to the shape of the weight distribution
Analog Bayesian neural networks are insensitive to the shape of the weight distribution
Ravi G. Patel
T. Xiao
S. Agarwal
C. Bennett
66
0
0
09 Jan 2025
Transferable Adversarial Examples with Bayes Approach
Transferable Adversarial Examples with Bayes Approach
Mingyuan Fan
Cen Chen
Ximeng Liu
Wenzhong Guo
AAML
125
1
0
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Low-Order Flow Reconstruction and Uncertainty Quantification in Disturbed Aerodynamics Using Sparse Pressure Measurements
Low-Order Flow Reconstruction and Uncertainty Quantification in Disturbed Aerodynamics Using Sparse Pressure Measurements
Hanieh Mousavi
J. Eldredge
40
3
0
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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
154
0
0
03 Jan 2025
Evidential Deep Learning for Probabilistic Modelling of Extreme Storm
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Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events
Ayush Khot
Xihaier Luo
Ai Kagawa
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EDLBDL
112
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0
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Learning Set Functions with Implicit Differentiation
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Gözde Özcan
Chengzhi Shi
Stratis Ioannidis
103
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Task Diversity in Bayesian Federated Learning: Simultaneous Processing
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Task Diversity in Bayesian Federated Learning: Simultaneous Processing of Classification and Regression
Junliang Lyu
Yixuan Zhang
Xiaoling Lu
Feng Zhou
FedML
139
1
0
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Enhance Vision-Language Alignment with Noise
Enhance Vision-Language Alignment with Noise
Sida Huang
Hongyuan Zhang
Xuelong Li
VLM
160
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A Decade of Deep Learning: A Survey on The Magnificent Seven
A Decade of Deep Learning: A Survey on The Magnificent Seven
Dilshod Azizov
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Deep Clustering using Dirichlet Process Gaussian Mixture and Alpha
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Deep evolving semi-supervised anomaly detection
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Investigating Plausibility of Biologically Inspired Bayesian Learning in
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Streamlining Prediction in Bayesian Deep Learning
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GraphGrad: Efficient Estimation of Sparse Polynomial Representations for
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162
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Revised Regularization for Efficient Continual Learning through
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136
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Yuxin Lin
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Shuo Shang
Rui Yan
AIFin
53
1
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GenJoin: Conditional Generative Plan-to-Plan Query Optimizer that Learns from Subplan Hints
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Claude Lehmann
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102
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Bayesian Controlled FDR Variable Selection via Knockoffs
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Anna Gottard
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48
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