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1503.08060
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Expectation Propagation in the large-data limit
27 March 2015
Guillaume P. Dehaene
Simon Barthelmé
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Papers citing
"Expectation Propagation in the large-data limit"
24 / 24 papers shown
Approximate Bayesian inference for cumulative probit regression models
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Streaming Factor Trajectory Learning for Temporal Tensor Decomposition
Neural Information Processing Systems (NeurIPS), 2023
Shikai Fang
Xin Yu
Shibo Li
Zheng Wang
R. Kirby
Shandian Zhe
AI4TS
252
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25 Oct 2023
Skewed Bernstein-von Mises theorem and skew-modal approximations
Annals of Statistics (Ann. Stat.), 2023
Daniele Durante
Francesco Pozza
Botond Szabó
544
15
0
08 Jan 2023
On the Approximation Accuracy of Gaussian Variational Inference
Annals of Statistics (Ann. Stat.), 2023
A. Katsevich
Philippe Rigollet
364
29
0
05 Jan 2023
Bayesian conjugacy in probit, tobit, multinomial probit and extensions: A review and new results
Journal of the American Statistical Association (JASA), 2022
Niccolò Anceschi
A. Fasano
Daniele Durante
T. Rigon
363
25
0
16 Jun 2022
Gaussian Process Regression in the Flat Limit
Annals of Statistics (Ann. Stat.), 2022
Simon Barthelmé
P. Amblard
Nicolas M Tremblay
K. Usevich
GP
364
6
0
04 Jan 2022
Bayes-Newton Methods for Approximate Bayesian Inference with PSD Guarantees
Journal of machine learning research (JMLR), 2021
William J. Wilkinson
Simo Särkkä
Arno Solin
BDL
345
18
0
02 Nov 2021
Sparse Algorithms for Markovian Gaussian Processes
International Conference on Artificial Intelligence and Statistics (AISTATS), 2021
William J. Wilkinson
Arno Solin
Vincent Adam
254
13
0
19 Mar 2021
Fast Approximate Bayesian Contextual Cold Start Learning (FAB-COST)
Jack R. McKenzie
Peter A. Appleby
T. House
N. Walton
111
0
0
18 Aug 2020
Infinite-dimensional gradient-based descent for alpha-divergence minimisation
Kamélia Daudel
Randal Douc
Franccois Portier
308
19
0
20 May 2020
Quantile Propagation for Wasserstein-Approximate Gaussian Processes
Neural Information Processing Systems (NeurIPS), 2019
Rui Zhang
Christian J. Walder
Edwin V. Bonilla
Marian-Andrei Rizoiu
Lexing Xie
296
2
0
21 Dec 2019
The
f
f
f
-Divergence Expectation Iteration Scheme
Kamélia Daudel
Randal Douc
Franccois Portier
François Roueff
260
1
0
26 Sep 2019
An innovative adaptive kriging approach for efficient binary classification of mechanical problems
J. Fuhg
A. Fau
AI4CE
110
2
0
02 Jul 2019
Universal Boosting Variational Inference
Neural Information Processing Systems (NeurIPS), 2019
Trevor Campbell
Xinglong Li
311
34
0
04 Jun 2019
Expectation Propagation for Poisson Data
Chen Zhang
Simon Arridge
Bangti Jin
192
13
0
18 Oct 2018
Approximate Collapsed Gibbs Clustering with Expectation Propagation
Christopher Aicher
E. Fox
147
0
0
19 Jul 2018
On numerical approximation schemes for expectation propagation
A. Roche
84
0
0
14 Nov 2016
Variational Inference via
χ
χ
χ
-Upper Bound Minimization
Adji Bousso Dieng
Dustin Tran
Rajesh Ranganath
John Paisley
David M. Blei
BDL
704
35
0
01 Nov 2016
Rényi Divergence Variational Inference
Yingzhen Li
Richard Turner
BDL
527
288
0
06 Feb 2016
Bounding errors of Expectation-Propagation
Guillaume P. Dehaene
Simon Barthelmé
203
25
0
11 Jan 2016
Distributed Bayesian Learning with Stochastic Natural-gradient Expectation Propagation and the Posterior Server
Leonard Hasenclever
Stefan Webb
Thibaut Lienart
Sebastian J. Vollmer
Balaji Lakshminarayanan
Charles Blundell
Yee Whye Teh
BDL
492
73
0
31 Dec 2015
Black-box
α
α
α
-divergence Minimization
José Miguel Hernández-Lobato
Yingzhen Li
Mark Rowland
Daniel Hernández-Lobato
T. Bui
Richard Turner
349
148
0
10 Nov 2015
Leave Pima Indians alone: binary regression as a benchmark for Bayesian computation
Nicolas Chopin
James Ridgway
244
80
0
29 Jun 2015
Stochastic Expectation Propagation
Neural Information Processing Systems (NeurIPS), 2015
Yingzhen Li
Jose Miguel Hernandez-Lobato
Richard Turner
357
120
0
12 Jun 2015
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