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Variational Inference: A Review for Statisticians

Variational Inference: A Review for Statisticians

4 January 2016
David M. Blei
A. Kucukelbir
Jon D. McAuliffe
    BDL
ArXivPDFHTML

Papers citing "Variational Inference: A Review for Statisticians"

50 / 1,816 papers shown
Title
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
71
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
66
1
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
45
0
0
28 Jan 2025
Bayesian Spatial Predictive Synthesis
Bayesian Spatial Predictive Synthesis
D. Cabel
S. Sugasawa
Masahiro Kato
K. Takanashi
K. McAlinn
113
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
57
0
0
28 Jan 2025
Information-theoretic Bayesian Optimization: Survey and Tutorial
Information-theoretic Bayesian Optimization: Survey and Tutorial
Eduardo C. Garrido-Merchán
67
0
0
22 Jan 2025
Globally Convergent Variational Inference
Globally Convergent Variational Inference
Declan McNamara
J. Loper
Jeffrey Regier
58
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
48
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
40
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
86
4
0
08 Jan 2025
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
0
0
03 Jan 2025
Evidential Deep Learning for Probabilistic Modelling of Extreme Storm
  Events
Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events
Ayush Khot
Xihaier Luo
Ai Kagawa
Shinjae Yoo
EDL
BDL
81
0
0
18 Dec 2024
Learning Set Functions with Implicit Differentiation
Learning Set Functions with Implicit Differentiation
Gözde Özcan
Chengzhi Shi
Stratis Ioannidis
69
0
0
15 Dec 2024
Task Diversity in Bayesian Federated Learning: Simultaneous Processing
  of Classification and Regression
Task Diversity in Bayesian Federated Learning: Simultaneous Processing of Classification and Regression
Junliang Lyu
Yixuan Zhang
Xiaoling Lu
Feng Zhou
FedML
80
1
0
14 Dec 2024
Enhance Vision-Language Alignment with Noise
Enhance Vision-Language Alignment with Noise
Sida Huang
Hongyuan Zhang
Xuelong Li
VLM
87
1
0
14 Dec 2024
A Decade of Deep Learning: A Survey on The Magnificent Seven
A Decade of Deep Learning: A Survey on The Magnificent Seven
Dilshod Azizov
Muhammad Arslan Manzoor
Velibor Bojkovic
Yingxu Wang
Zhilin Wang
...
Liang Li
Siwei Liu
Yu Zhong
Wei Liu
Shangsong Liang
OOD
AI4TS
MedIm
129
0
0
13 Dec 2024
Deep Clustering using Dirichlet Process Gaussian Mixture and Alpha
  Jensen-Shannon Divergence Clustering Loss
Deep Clustering using Dirichlet Process Gaussian Mixture and Alpha Jensen-Shannon Divergence Clustering Loss
Kart-Leong Lim
BDL
84
0
0
12 Dec 2024
Deep evolving semi-supervised anomaly detection
Deep evolving semi-supervised anomaly detection
Jack Belham
Aryan Bhosale
Samrat Mukherjee
Biplab Banerjee
Fabio Cuzzolin
75
0
0
01 Dec 2024
Investigating Plausibility of Biologically Inspired Bayesian Learning in
  ANNs
Investigating Plausibility of Biologically Inspired Bayesian Learning in ANNs
Ram Zaveri
CLL
70
0
0
27 Nov 2024
Streamlining Prediction in Bayesian Deep Learning
Streamlining Prediction in Bayesian Deep Learning
Rui Li
Marcus Klasson
Arno Solin
Martin Trapp
UQCV
BDL
102
2
0
27 Nov 2024
GraphGrad: Efficient Estimation of Sparse Polynomial Representations for
  General State-Space Models
GraphGrad: Efficient Estimation of Sparse Polynomial Representations for General State-Space Models
Benjamin Cox
Émilie Chouzenoux
Victor Elvira
81
0
0
23 Nov 2024
Revised Regularization for Efficient Continual Learning through
  Correlation-Based Parameter Update in Bayesian Neural Networks
Revised Regularization for Efficient Continual Learning through Correlation-Based Parameter Update in Bayesian Neural Networks
Sanchar Palit
Biplab Banerjee
S. Chaudhuri
CLL
83
0
0
21 Nov 2024
Variational Bayesian Bow tie Neural Networks with Shrinkage
Alisa Sheinkman
Sara Wade
BDL
UQCV
51
0
0
17 Nov 2024
CausalStock: Deep End-to-end Causal Discovery for News-driven Stock
  Movement Prediction
CausalStock: Deep End-to-end Causal Discovery for News-driven Stock Movement Prediction
Shuqi Li
Yuebo Sun
Yuxin Lin
Xin Gao
Shuo Shang
Rui Yan
AIFin
31
1
0
10 Nov 2024
Bayesian Controlled FDR Variable Selection via Knockoffs
Bayesian Controlled FDR Variable Selection via Knockoffs
Lorenzo Focardi-Olmi
Anna Gottard
Michele Guindani
Marina Vannucci
41
0
0
05 Nov 2024
Stein Variational Newton Neural Network Ensembles
Stein Variational Newton Neural Network Ensembles
Klemens Flöge
Mohammed Abdul Moeed
Vincent Fortuin
BDL
UQCV
37
0
0
04 Nov 2024
Analyzing Multimodal Integration in the Variational Autoencoder from an
  Information-Theoretic Perspective
Analyzing Multimodal Integration in the Variational Autoencoder from an Information-Theoretic Perspective
Carlotta Langer
Yasmin Kim Georgie
Ilja Porohovoj
Verena V. Hafner
Nihat Ay
DRL
34
1
0
01 Nov 2024
Adaptive Residual Transformation for Enhanced Feature-Based OOD
  Detection in SAR Imagery
Adaptive Residual Transformation for Enhanced Feature-Based OOD Detection in SAR Imagery
Kyung-Hwan Lee
Kyung-Tae Kim
26
0
0
01 Nov 2024
Inclusive KL Minimization: A Wasserstein-Fisher-Rao Gradient Flow
  Perspective
Inclusive KL Minimization: A Wasserstein-Fisher-Rao Gradient Flow Perspective
Jia-Jie Zhu
78
1
0
31 Oct 2024
Multi-environment Topic Models
Multi-environment Topic Models
Dominic Sobhani
Amir Feder
David M. Blei
30
0
0
31 Oct 2024
EigenVI: score-based variational inference with orthogonal function
  expansions
EigenVI: score-based variational inference with orthogonal function expansions
Diana Cai
Chirag Modi
C. Margossian
Robert Mansel Gower
David M. Blei
Lawrence K. Saul
BDL
42
5
0
31 Oct 2024
Functional Gradient Flows for Constrained Sampling
Functional Gradient Flows for Constrained Sampling
Shiyue Zhang
Longlin Yu
Ziheng Cheng
Cheng Zhang
39
0
0
30 Oct 2024
ELBOing Stein: Variational Bayes with Stein Mixture Inference
ELBOing Stein: Variational Bayes with Stein Mixture Inference
Ola Rønning
Eric T. Nalisnick
Christophe Ley
Padhraic Smyth
Thomas Hamelryck
BDL
55
1
0
30 Oct 2024
SimSiam Naming Game: A Unified Approach for Representation Learning and
  Emergent Communication
SimSiam Naming Game: A Unified Approach for Representation Learning and Emergent Communication
Nguyen Le Hoang
T. Taniguchi
Fang Tianwei
Akira Taniguchi
36
1
0
29 Oct 2024
Batch, match, and patch: low-rank approximations for score-based variational inference
Batch, match, and patch: low-rank approximations for score-based variational inference
Chirag Modi
Diana Cai
Lawrence K. Saul
BDL
39
1
0
29 Oct 2024
Hierarchical mixtures of Unigram models for short text clustering: The role of Beta-Liouville priors
Hierarchical mixtures of Unigram models for short text clustering: The role of Beta-Liouville priors
Massimo Bilancia
Samuele Magro
38
0
0
29 Oct 2024
Likelihood approximations via Gaussian approximate inference
Likelihood approximations via Gaussian approximate inference
Thang D. Bui
35
0
0
28 Oct 2024
Noise-Aware Differentially Private Variational Inference
Noise-Aware Differentially Private Variational Inference
Talal Alrawajfeh
Joonas Jälkö
Antti Honkela
35
0
0
25 Oct 2024
Brain-like variational inference
Brain-like variational inference
Hadi Vafaii
Dekel Galor
Jacob L. Yates
DRL
49
0
0
25 Oct 2024
An Investigation on Machine Learning Predictive Accuracy Improvement and
  Uncertainty Reduction using VAE-based Data Augmentation
An Investigation on Machine Learning Predictive Accuracy Improvement and Uncertainty Reduction using VAE-based Data Augmentation
Farah Alsafadi
M. Yaseen
Xu Wu
24
0
0
24 Oct 2024
Evolving Voices Based on Temporal Poisson Factorisation
Evolving Voices Based on Temporal Poisson Factorisation
Jan Vávra
Bettina Grün
Paul Hofmarcher
21
1
0
24 Oct 2024
Scalable Random Feature Latent Variable Models
Scalable Random Feature Latent Variable Models
Ying Li
Zhidi Lin
Yuhao Liu
Michael Minyi Zhang
Pablo Martínez Olmos
Petar M. Djurić
BDL
DRL
33
0
0
23 Oct 2024
Reinforced Imitative Trajectory Planning for Urban Automated Driving
Reinforced Imitative Trajectory Planning for Urban Automated Driving
Di Zeng
Ling Zheng
Xiantong Yang
Yinong Li
31
0
0
21 Oct 2024
Modeling Dynamic Neural Activity by combining Naturalistic Video Stimuli and Stimulus-independent Latent Factors
Modeling Dynamic Neural Activity by combining Naturalistic Video Stimuli and Stimulus-independent Latent Factors
Finn Schmidt
Suhas Shrinivasan
Polina Turishcheva
Fabian H. Sinz
53
0
0
21 Oct 2024
HyQE: Ranking Contexts with Hypothetical Query Embeddings
HyQE: Ranking Contexts with Hypothetical Query Embeddings
Weichao Zhou
Jiaxin Zhang
Hilaf Hasson
Anu Singh
Wenchao Li
RALM
30
1
0
20 Oct 2024
Predictive variational inference: Learn the predictively optimal posterior distribution
Predictive variational inference: Learn the predictively optimal posterior distribution
Jinlin Lai
Yuling Yao
BDL
31
0
0
18 Oct 2024
Unscrambling disease progression at scale: fast inference of event
  permutations with optimal transport
Unscrambling disease progression at scale: fast inference of event permutations with optimal transport
P. Wijeratne
Daniel C. Alexander
25
0
0
18 Oct 2024
Annealed Stein Variational Gradient Descent for Improved Uncertainty
  Estimation in Full-Waveform Inversion
Annealed Stein Variational Gradient Descent for Improved Uncertainty Estimation in Full-Waveform Inversion
M. Corrales
Sean Berti
Bertrand Denel
Paul Williamson
Mattia Aleardi
M. Ravasi
24
1
0
17 Oct 2024
Navigation under uncertainty: Trajectory prediction and occlusion
  reasoning with switching dynamical systems
Navigation under uncertainty: Trajectory prediction and occlusion reasoning with switching dynamical systems
Ran Wei
Joseph Lee
Shohei Wakayama
Alexander Tschantz
Conor Heins
...
Mahault Albarracin
Miguel de Prado
Petter Horling
Peter Winzell
Renjith Rajagopal
33
2
0
14 Oct 2024
A Structural Text-Based Scaling Model for Analyzing Political Discourse
A Structural Text-Based Scaling Model for Analyzing Political Discourse
Jan Vávra
Bernd Hans-Konrad Prostmaier
Bettina Grün
Paul Hofmarcher
21
1
0
14 Oct 2024
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