Bo Wang
Bo Wang
Department of Mathematics, University of Leicester, UK
Verified email at le.ac.uk - Homepage
Title
Cited by
Cited by
Year
Convergence properties of a general algorithm for calculating variational Bayesian estimates for a normal mixture model
B Wang, DM Titterington
Bayesian Analysis 1 (3), 625-650, 2006
1292006
Inadequacy of interval estimates corresponding to variational Bayesian approximations.
B Wang, DM Titterington
AISTATS, 373-380, 2005
1052005
Gaussian process functional regression modeling for batch data
JQ Shi, B Wang, R Murray‐Smith, DM Titterington
Biometrics 63 (3), 714-723, 2007
932007
Convergence and asymptotic normality of variational Bayesian approximations for exponential family models with missing values
B Wang, DM Titterington
Proceedings of the 20th conference on Uncertainty in artificial intelligence …, 2004
74*2004
Curve prediction and clustering with mixtures of Gaussian process functional regression models
JQ Shi, B Wang
Statistics and Computing 18 (3), 267-283, 2008
702008
Infinite time interval BSDEs and the convergence of g-martingales
Z Chen, B Wang
Journal of the Australian Mathematical Society (Series A) 69 (02), 187-211, 2000
632000
The role of host and microbial factors in the pathogenesis of pneumococcal bacteraemia arising from a single bacterial cell bottleneck
A. Gerlini, L. Colomba, L. Furi, T. Braccini, A.S. Manso, A. Pammolli, Bo ...
PLoS Pathogens 10 (3), 2014
442014
Generalized Gaussian Process Regression Model for Non-Gaussian Functional Data
B Wang, JQ Shi
Journal of the American Statistical Association 109 (507), 1123-1133, 2014
442014
Lack of consistency of mean field and variational Bayes approximations for state space models
B Wang, DM Titterington
Neural processing letters 20 (3), 151-170, 2004
432004
Gaussian process regression with multiple response variables
B Wang, T Chen
Chemometrics and Intelligent Laboratory Systems 142, 159-165, 2015
422015
Mixed‐effects Gaussian process functional regression models with application to dose–response curve prediction
JQ Shi, B Wang, EJ Will, RM West
Statistics in Medicine 31 (26), 3165-3177, 2012
412012
Bayesian variable selection for Gaussian process regression: Application to chemometric calibration of spectrometers
T Chen, B Wang
Neurocomputing 73 (13-15), 2718-2726, 2010
362010
A Gaussian process regression approach to a single-index model
T Choi, JQ Shi, B Wang
Journal of Nonparametric Statistics 23 (1), 21-36, 2011
352011
How priors of initial hyperparameters affect Gaussian process regression models
Z Chen, B Wang
Neurocomputing 275, 1702-1710, 2018
302018
Multivariate Gaussian and Student-t process regression for multi-output prediction
Z Chen, B Wang, AN Gorban
Neural Computing and Applications 32 (8), 3005-3028, 2020
262020
Re: A randomized controlled trial comparing fresh, dried and dried‐then‐rehydrated temporalis fascia in myringoplasty
N Sethi, Y Bajaj, B Wang, S Gunasekaran, A Coatesworth
Clinical Otolaryngology 33 (5), 496-497, 2008
22*2008
Kriging meta‐model assisted calibration of computational fluid dynamics models
OT Kajero, RB Thorpe, T Chen, B Wang, Y Yao
AIChE Journal 62 (12), 4308-4320, 2016
172016
Gaussian process regression method for forecasting of mortality rates
R Wu, B Wang
Neurocomputing 316, 232-239, 2018
112018
Variational bayes estimation of mixing coefficients
B Wang, D Titterington
Deterministic and statistical methods in machine learning, 281-295, 2005
112005
Gaussian process regression with functional covariates and multivariate response
B Wang, T Chen, A Xu
Chemometrics and Intelligent Laboratory Systems 163, 1-6, 2017
82017
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Articles 1–20