NEW ADVANCES IN BAYESIAN INFERENCE FOR GAUSSIAN PROCESS AND DEEP GAUSSIAN PROCESS MODELS

Ph.D

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Main Author: YU HAIBIN
Other Authors: COMPUTER SCIENCE
Published: 2020
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Online Access:https://scholarbank.nus.edu.sg/handle/10635/168231
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Institution: National University of Singapore
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spelling sg-nus-scholar.10635-1682312021-12-14T18:00:23Z NEW ADVANCES IN BAYESIAN INFERENCE FOR GAUSSIAN PROCESS AND DEEP GAUSSIAN PROCESS MODELS YU HAIBIN COMPUTER SCIENCE Low Kian Hsiang PATRICK JAILLET Bayeisan machine learning, Gaussian process, deep Gaussian process, variational inference Ph.D DOCTOR OF PHILOSOPHY (SOC) 2020-05-18T18:00:24Z 2020-05-18T18:00:24Z 2020-01-17 YU HAIBIN (2020-01-17). NEW ADVANCES IN BAYESIAN INFERENCE FOR GAUSSIAN PROCESS AND DEEP GAUSSIAN PROCESS MODELS. ScholarBank@NUS Repository. https://scholarbank.nus.edu.sg/handle/10635/168231 0000-0001-7723-6511
institution National University of Singapore
building NUS Library
continent Asia
country Singapore
Singapore
content_provider NUS Library
collection ScholarBank@NUS
topic Bayeisan machine learning, Gaussian process, deep Gaussian process, variational inference
spellingShingle Bayeisan machine learning, Gaussian process, deep Gaussian process, variational inference
YU HAIBIN
NEW ADVANCES IN BAYESIAN INFERENCE FOR GAUSSIAN PROCESS AND DEEP GAUSSIAN PROCESS MODELS
description Ph.D
author2 COMPUTER SCIENCE
author_facet COMPUTER SCIENCE
YU HAIBIN
author YU HAIBIN
author_sort YU HAIBIN
title NEW ADVANCES IN BAYESIAN INFERENCE FOR GAUSSIAN PROCESS AND DEEP GAUSSIAN PROCESS MODELS
title_short NEW ADVANCES IN BAYESIAN INFERENCE FOR GAUSSIAN PROCESS AND DEEP GAUSSIAN PROCESS MODELS
title_full NEW ADVANCES IN BAYESIAN INFERENCE FOR GAUSSIAN PROCESS AND DEEP GAUSSIAN PROCESS MODELS
title_fullStr NEW ADVANCES IN BAYESIAN INFERENCE FOR GAUSSIAN PROCESS AND DEEP GAUSSIAN PROCESS MODELS
title_full_unstemmed NEW ADVANCES IN BAYESIAN INFERENCE FOR GAUSSIAN PROCESS AND DEEP GAUSSIAN PROCESS MODELS
title_sort new advances in bayesian inference for gaussian process and deep gaussian process models
publishDate 2020
url https://scholarbank.nus.edu.sg/handle/10635/168231
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