The Probability Companion for Engineering and Computer Science

DOI10.1017/9781108635349zbMath1456.60001OpenAlexW3000469744MaRDI QIDQ5377009

Adam Prügel-Bennett

Publication date: 21 May 2019

Full work available at URL: https://doi.org/10.1017/9781108635349

zbMATH Keywords

hidden Markov modelcentral limit theoremmaximum likelihoodKullback-Leibler divergenceextreme value distributionBayesian inferencemultivariate normal distributiongraphical modelprobabilistic modellatent Dirichlet allocationmultinormal distributionlarge deviation boundsStudent's T distributionWasserstein generative adversarial networksprobabilistic and Bayesian networksF-textmachine learning and deep learning

Mathematics Subject Classification ID

Gaussian processes (60G15) Applications of statistics in engineering and industry; control charts (62P30) Introductory exposition (textbooks, tutorial papers, etc.) pertaining to probability theory (60-01) Applications of Markov chains and discrete-time Markov processes on general state spaces (social mobility, learning theory, industrial processes, etc.) (60J20) Mathematics for nonmathematicians (engineering, social sciences, etc.) (00A06) Introductory exposition (textbooks, tutorial papers, etc.) pertaining to mathematics in general (00-01)

This page was built for publication: The Probability Companion for Engineering and Computer Science