VARIATIONAL BAYES METHODS IN GAUSSIAN PROCESS REGRESSION

VARIATIONAL BAYES METHODS IN GAUSSIAN PROCESS REGRESSION

Ph.D

Saved in:

Bibliographic Details
Main Author:	MENSAH DAVID KWAMENA
Other Authors:	STATISTICS & APPLIED PROBABILITY
Format:	Theses and Dissertations
Language:	English
Published:	2016
Subjects:	Variational Bayes, Gaussian processes, shape restricted regression, longitudinal data, functional data, functional mixtures
Online Access:	http://scholarbank.nus.edu.sg/handle/10635/124177
Tags:	Add Tag No Tags, Be the first to tag this record!
Institution:	National University of Singapore
Language:	English

Similar Items

MAP approximation to the variational Bayes Gaussian mixture model and application
by: Lim, Kart-Leong, et al.
Published: (2020)

Variational inference for generalized linear mixed models using partially noncentered parametrizations
by: Tan, L.S.L., et al.
Published: (2014)

p-Variation of gaussian processes with stationary increments
by: Shao, Q.-M.
Published: (2014)

Regression density estimation with variational methods and stochastic approximation
by: Nott, D.J., et al.
Published: (2014)

When Gaussian process meets big data : a review of scalable GPs
by: Liu, Haitao, et al.
Published: (2021)

Understanding and comparing scalable Gaussian process regression for big data
by: Liu, Haitao, et al.
Published: (2020)

NEW ADVANCES IN BAYESIAN INFERENCE FOR GAUSSIAN PROCESS AND DEEP GAUSSIAN PROCESS MODELS
by: YU HAIBIN
Published: (2020)

Effects of variance-function misspecification in analysis of longitudinal data
by: Wang, Y.-G., et al.
Published: (2014)

Smoothing combined estimating equations in quantile regression for longitudinal data
by: Leng, C., et al.
Published: (2014)

Empirical likelihood and quantile regression in longitudinal data analysis
by: Tang, C.Y., et al.
Published: (2014)

Variational Approximation for Complex Regression Models
by: TAN SIEW LI, LINDA
Published: (2013)

Efficient estimation for covariance parameters in analysis of longitudinal data
by: ZHAO YUNING
Published: (2010)

Nonrigid Shape Recovery by Gaussian Process Regression
by: ZHU, Jianke, et al.
Published: (2009)

Weighted rank regression for clustered data analysis
by: Wang, Y.-G., et al.
Published: (2016)

Approximation of Gaussian by scaling functions and biorthogonal scaling polynomials
by: Lee, S.L.
Published: (2014)

Structural Nonparametric Cointegrating Regression
by: Wang, Q. Y., et al.
Published: (2009)

Statistical inferences for linear models with functional responses
by: Zhang, J.-T.
Published: (2014)

Pointwise bound of SO(d,C) -invariant holomorphic functions which are square-integrable with respect to a gaussian measure
by: Areerak Kaewthep
Published: (2008)

Bayesian updating of model parameters using adaptive Gaussian process regression and particle filter
by: Yoshida, Ikumasa, et al.
Published: (2023)

NON-STATIONARY GAUSSIAN PROCESS MODELS FOR DETERMINISTIC AND STOCHASTIC SIMULATION
by: YANG LINCHANG
Published: (2016)

Cope with diverse data structures in multi-fidelity modeling : a Gaussian process method
by: Liu, Haitao, et al.
Published: (2020)

Data fusion in radial basis function networks for spatial regression
by: Hu, T., et al.
Published: (2013)

Lower bound on averages of the product of L Gaussian Q-functions over Nakagami-m Fading
by: Fu, H., et al.
Published: (2014)

Easy-but-effective domain sub-similarity learning for transfer regression
by: Wei, Pengfei, et al.
Published: (2021)

Joint estimation of covariance matrix via Cholesky Decomposition
by: JIANG XIAOJUN
Published: (2012)

Infeasibility and efficiency of working correlation matrix in generalized estimating equations
by: NG WEE TECK
Published: (2011)

Unbiased estimating equations from working correlation models for irregularly timed repeated measures
by: Wang, Y.-G., et al.
Published: (2014)

Robust estimating functions and bias correction for longitudinal data analysis
by: Wang, Y.-G., et al.
Published: (2014)

Bayesian support vector regression using a unified loss function
by: Chu, W., et al.
Published: (2014)

Asymptotically refined score and GOF tests for inverse Gaussian models
by: DESMOND, Anthony F., et al.
Published: (2016)

Remarks on multi-output Gaussian process regression
by: Liu, Haitao, et al.
Published: (2020)

Assessment of Expressway Traffic Safety Using Gaussian Mixture Model based on Time to Collision
by: Jin, S., et al.
Published: (2014)

A sequential feature extraction approach for naïve bayes classification of microarray data
by: Fan, L., et al.
Published: (2014)

Gaussian mixture probability hypothesis density for visual people tracking
by: Wang, Y.-D., et al.
Published: (2014)

MULTI-FIDELITY OPTIMIZATION WITH GAUSSIAN REGRESSION ON ORDINAL TRANSFORMATION SPACE
by: CHEN MIN
Published: (2017)

Working correlation structure misspecification, estimation and covariate design: Implications for generalised estimating equations performance
by: Wang, Y.-G., et al.
Published: (2014)

Fast image restoration methods for impulse and Gaussian noises removal
by: Huang, Y.-M., et al.
Published: (2014)

Distributed Data Reconciliation And Bias Estimation With Non-Gaussian Noise For Sensor Network
by: JOE YEN YEN
Published: (2010)

A two-stage speaker adaptation approach for subspace gaussian mixture model based nonnative speech recognition
by: Li, B., et al.
Published: (2014)

Averages of the product of two Gaussian Q-functions over fading statistics and applications
by: Li, R., et al.
Published: (2014)