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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
Adversarially-regularized mixed effects deep learning (ARMED) models for
  improved interpretability, performance, and generalization on clustered data
Adversarially-regularized mixed effects deep learning (ARMED) models for improved interpretability, performance, and generalization on clustered data
K. Nguyen
A. Montillo
FedMLAAML
72
10
0
23 Feb 2022
Using Bayesian Deep Learning to infer Planet Mass from Gaps in
  Protoplanetary Disks
Using Bayesian Deep Learning to infer Planet Mass from Gaps in Protoplanetary Disks
Sayantan Auddy
Ramit Dey
Min-Kai Lin
D. Carrera
J. Simon
UQCVBDL
47
4
0
23 Feb 2022
Cyclical Variational Bayes Monte Carlo for Efficient Multi-Modal
  Posterior Distributions Evaluation
Cyclical Variational Bayes Monte Carlo for Efficient Multi-Modal Posterior Distributions Evaluation
F. Igea
Alice Cicirello
61
8
0
23 Feb 2022
A Bayesian Deep Learning Approach to Near-Term Climate Prediction
A Bayesian Deep Learning Approach to Near-Term Climate Prediction
Xihaier Luo
Balasubramanya T. Nadiga
Yihui Ren
Ji Hwan Park
Wei Xu
Shinjae Yoo
BDLAI4CE
68
12
0
23 Feb 2022
Multiple Importance Sampling ELBO and Deep Ensembles of Variational
  Approximations
Multiple Importance Sampling ELBO and Deep Ensembles of Variational Approximations
Oskar Kviman
Harald Melin
Hazal Koptagel
Victor Elvira
J. Lagergren
DRL
134
17
0
22 Feb 2022
Stochastic Modeling of Inhomogeneities in the Aortic Wall and
  Uncertainty Quantification using a Bayesian Encoder-Decoder Surrogate
Stochastic Modeling of Inhomogeneities in the Aortic Wall and Uncertainty Quantification using a Bayesian Encoder-Decoder Surrogate
Sascha Ranftl
Malte Rolf-Pissarczyk
G. Wolkerstorfer
Antonio Pepe
Jan Egger
W. Linden
G. Holzapfel
75
9
0
21 Feb 2022
Truncated Diffusion Probabilistic Models and Diffusion-based Adversarial
  Auto-Encoders
Truncated Diffusion Probabilistic Models and Diffusion-based Adversarial Auto-Encoders
Huangjie Zheng
Pengcheng He
Weizhu Chen
Mingyuan Zhou
DiffM
92
46
0
19 Feb 2022
Fast online inference for nonlinear contextual bandit based on
  Generative Adversarial Network
Fast online inference for nonlinear contextual bandit based on Generative Adversarial Network
Yun-Da Tsai
Shou-De Lin
80
5
0
17 Feb 2022
Hybridizing Physical and Data-driven Prediction Methods for
  Physicochemical Properties
Hybridizing Physical and Data-driven Prediction Methods for Physicochemical Properties
Fabian Jirasek
Robert Bamler
Stephan Mandt
AI4CE
49
16
0
17 Feb 2022
Deep learning and differential equations for modeling changes in
  individual-level latent dynamics between observation periods
Deep learning and differential equations for modeling changes in individual-level latent dynamics between observation periods
G. Köber
R. Kalisch
Lara Puhlmann
A. Chmitorz
Anita Schick
Harald Binder
56
1
0
15 Feb 2022
Flexible learning of quantum states with generative query neural
  networks
Flexible learning of quantum states with generative query neural networks
Yan Zhu
Yadong Wu
Ge Bai
Dongsheng Wang
Yuexuan Wang
G. Chiribella
77
36
0
14 Feb 2022
Reinforcement Learning in Presence of Discrete Markovian Context
  Evolution
Reinforcement Learning in Presence of Discrete Markovian Context Evolution
Hang Ren
Aivar Sootla
Taher Jafferjee
Junxiao Shen
Jun Wang
Haitham Bou-Ammar
BDLOffRL
80
11
0
14 Feb 2022
Improving Generalization via Uncertainty Driven Perturbations
Improving Generalization via Uncertainty Driven Perturbations
Matteo Pagliardini
Gilberto Manunza
Martin Jaggi
Michael I. Jordan
Tatjana Chavdarova
AAMLAI4CE
85
4
0
11 Feb 2022
Bernstein Flows for Flexible Posteriors in Variational Bayes
Bernstein Flows for Flexible Posteriors in Variational Bayes
Oliver Durr
Stephan Hörling
Daniel Dold
Ivonne Kovylov
Beate Sick
BDL
102
4
0
11 Feb 2022
Grassmann Stein Variational Gradient Descent
Grassmann Stein Variational Gradient Descent
Xingtu Liu
Harrison Zhu
Jean-François Ton
George Wynne
Andrew Duncan
97
12
0
07 Feb 2022
Nonparametric Uncertainty Quantification for Single Deterministic Neural
  Network
Nonparametric Uncertainty Quantification for Single Deterministic Neural Network
Nikita Kotelevskii
A. Artemenkov
Kirill Fedyanin
Fedor Noskov
Alexander Fishkov
Artem Shelmanov
Artem Vazhentsev
Aleksandr Petiushko
Maxim Panov
UQCVBDL
108
30
0
07 Feb 2022
BAM: Bayes with Adaptive Memory
BAM: Bayes with Adaptive Memory
Josue Nassar
Jennifer Brennan
Ben Evans
Kendall Lowrey
CLLKELM
55
1
0
04 Feb 2022
De-Sequentialized Monte Carlo: a parallel-in-time particle smoother
De-Sequentialized Monte Carlo: a parallel-in-time particle smoother
Adrien Corenflos
Nicolas Chopin
Simo Särkkä
72
7
0
04 Feb 2022
Transport Score Climbing: Variational Inference Using Forward KL and
  Adaptive Neural Transport
Transport Score Climbing: Variational Inference Using Forward KL and Adaptive Neural Transport
Liyi Zhang
David M. Blei
C. A. Naesseth
74
7
0
03 Feb 2022
Incorporating Sum Constraints into Multitask Gaussian Processes
Incorporating Sum Constraints into Multitask Gaussian Processes
Philipp Pilar
Carl Jidling
Thomas B. Schon
Niklas Wahlström
TPM
67
3
0
03 Feb 2022
Posterior temperature optimized Bayesian models for inverse problems in
  medical imaging
Posterior temperature optimized Bayesian models for inverse problems in medical imaging
M. Laves
Malte Tolle
Alexander Schlaefer
Sandy Engelhardt
78
10
0
02 Feb 2022
AdaAnn: Adaptive Annealing Scheduler for Probability Density
  Approximation
AdaAnn: Adaptive Annealing Scheduler for Probability Density Approximation
Emma R. Cobian
J. Hauenstein
Fang Liu
Daniele E. Schiavazzi
65
4
0
01 Feb 2022
Tutorial on amortized optimization
Tutorial on amortized optimization
Brandon Amos
OffRL
177
48
0
01 Feb 2022
A heteroencoder architecture for prediction of failure locations in
  porous metals using variational inference
A heteroencoder architecture for prediction of failure locations in porous metals using variational inference
Wyatt Bridgman
Xiaoxuan Zhang
G. Teichert
M. Khalil
K. Garikipati
Reese E. Jones
UQCVAI4CE
72
5
0
31 Jan 2022
Optimal Regret Is Achievable with Bounded Approximate Inference Error:
  An Enhanced Bayesian Upper Confidence Bound Framework
Optimal Regret Is Achievable with Bounded Approximate Inference Error: An Enhanced Bayesian Upper Confidence Bound Framework
Ziyi Huang
Henry Lam
A. Meisami
Haofeng Zhang
111
4
0
31 Jan 2022
Graph Representation Learning via Aggregation Enhancement
Graph Representation Learning via Aggregation Enhancement
Maxim Fishman
Chaim Baskin
Evgenii Zheltonozhskii
Almog David
Ron Banner
A. Mendelson
104
0
0
30 Jan 2022
Bayesian Nonlinear Models for Repeated Measurement Data: An Overview,
  Implementation, and Applications
Bayesian Nonlinear Models for Repeated Measurement Data: An Overview, Implementation, and Applications
Se Yoon Lee
109
19
0
28 Jan 2022
Variational Model Inversion Attacks
Variational Model Inversion Attacks
Kuan-Chieh Wang
Yanzhe Fu
Ke Li
Ashish Khisti
R. Zemel
Alireza Makhzani
MIACV
94
99
0
26 Jan 2022
Simpler is better: spectral regularization and up-sampling techniques
  for variational autoencoders
Simpler is better: spectral regularization and up-sampling techniques for variational autoencoders
Sara Bjork
Jonas Nordhaug Myhre
T. Johansen
DRL
79
6
0
19 Jan 2022
Alleviating Cold-start Problem in CTR Prediction with A Variational
  Embedding Learning Framework
Alleviating Cold-start Problem in CTR Prediction with A Variational Embedding Learning Framework
Xiaoxiao Xu
Chen Yang
Qian Yu
Zhiwei Fang
Jiaxing Wang
Chaosheng Fan
Yang He
Changping Peng
Zhangang Lin
Jingping Shao
CML
49
28
0
17 Jan 2022
Robust uncertainty estimates with out-of-distribution pseudo-inputs
  training
Robust uncertainty estimates with out-of-distribution pseudo-inputs training
Pierre Segonne
Yevgen Zainchkovskyy
Søren Hauberg
UQCVOOD
26
1
0
15 Jan 2022
Multi-task longitudinal forecasting with missing values on Alzheimer's
  Disease
Multi-task longitudinal forecasting with missing values on Alzheimer's Disease
C. Sevilla-Salcedo
Vandad Imani
Pablo Martínez Olmos
Vanessa Gómez-Verdejo
Jussi Tohka
57
8
0
13 Jan 2022
Loss-calibrated expectation propagation for approximate Bayesian
  decision-making
Loss-calibrated expectation propagation for approximate Bayesian decision-making
Michael J. Morais
Jonathan W. Pillow
84
6
0
10 Jan 2022
Preserving Domain Private Representation via Mutual Information
  Maximization
Preserving Domain Private Representation via Mutual Information Maximization
Jiahong Chen
Jing Wang
Weipeng Lin
Kuangen Zhang
Clarence W. de Silva
OOD
55
4
0
09 Jan 2022
Bayesian Neural Hawkes Process for Event Uncertainty Prediction
Bayesian Neural Hawkes Process for Event Uncertainty Prediction
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Ragja Palakkadavath
P. K. Srijith
BDL
63
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0
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Latent Time Neural Ordinary Differential Equations
Latent Time Neural Ordinary Differential Equations
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P. K. Srijith
BDL
46
5
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Improving Robustness and Uncertainty Modelling in Neural Ordinary
  Differential Equations
Improving Robustness and Uncertainty Modelling in Neural Ordinary Differential Equations
Srinivas Anumasa
P. K. Srijith
OODUQCVBDL
81
11
0
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The interplay between ranking and communities in networks
The interplay between ranking and communities in networks
Laura Iacovissi
Caterina De Bacco
142
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0
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Surrogate Likelihoods for Variational Annealed Importance Sampling
Surrogate Likelihoods for Variational Annealed Importance Sampling
M. Jankowiak
Du Phan
BDL
87
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0
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Transformers Can Do Bayesian Inference
Transformers Can Do Bayesian Inference
Samuel G. Müller
Noah Hollmann
Sebastian Pineda Arango
Josif Grabocka
Frank Hutter
BDLUQCV
113
170
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Projected Sliced Wasserstein Autoencoder-based Hyperspectral Images Anomaly Detection
Yurong Chen
Hui Zhang
Yaonan Wang
Q. M. J. Wu
Yimin Yang
56
0
0
20 Dec 2021
Approximating Bayes in the 21st Century
Approximating Bayes in the 21st Century
G. Martin
David T. Frazier
Christian P. Robert
83
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Variational Bayes for high-dimensional proportional hazards models with
  applications within gene expression
Variational Bayes for high-dimensional proportional hazards models with applications within gene expression
M. Komodromos
E. Aboagye
Marina Evangelou
Sarah Filippi
Kolyan Ray
81
10
0
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QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in
  Brain Tumor Segmentation - Analysis of Ranking Scores and Benchmarking
  Results
QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation - Analysis of Ranking Scores and Benchmarking Results
Raghav Mehta
Angelos Filos
Ujjwal Baid
C. Sako
Richard McKinley
...
Christos Davatzikos
Bjoern Menze
Spyridon Bakas
Y. Gal
Tal Arbel
UQCV
112
49
0
19 Dec 2021
Biased Gradient Estimate with Drastic Variance Reduction for Meta
  Reinforcement Learning
Biased Gradient Estimate with Drastic Variance Reduction for Meta Reinforcement Learning
Yunhao Tang
68
7
0
14 Dec 2021
Spatial-Temporal-Fusion BNN: Variational Bayesian Feature Layer
Spatial-Temporal-Fusion BNN: Variational Bayesian Feature Layer
Shiye Lei
Zhuozhuo Tu
Leszek Rutkowski
Feng Zhou
Li Shen
Fengxiang He
Dacheng Tao
BDL
80
2
0
12 Dec 2021
Programming with Neural Surrogates of Programs
Programming with Neural Surrogates of Programs
Alex Renda
Yi Ding
Michael Carbin
38
4
0
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A Sparse Expansion For Deep Gaussian Processes
A Sparse Expansion For Deep Gaussian Processes
Liang Ding
Rui Tuo
Shahin Shahrampour
68
6
0
11 Dec 2021
The Peril of Popular Deep Learning Uncertainty Estimation Methods
The Peril of Popular Deep Learning Uncertainty Estimation Methods
Yehao Liu
Matteo Pagliardini
Tatjana Chavdarova
Sebastian U. Stich
UQCV
38
16
0
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Traversing Time with Multi-Resolution Gaussian Process State-Space
  Models
Traversing Time with Multi-Resolution Gaussian Process State-Space Models
Krista Longi
J. Lindinger
Olaf Duennbier
M. Kandemir
Arto Klami
Barbara Rakitsch
52
3
0
06 Dec 2021
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