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Showing 1 - 12 of 12 results for “mark girolami”
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  • Handbook of Statistical Systems Biology

    by Michael Stumpf, David J. Balding, Mark Girolami ...
    Systems Biology is now entering a mature phase in which the key issues are characterising uncertainty and stochastic effects in mathematical models of biological systems. The area is moving towards a full statistical analysis and probabilistic reasoning over the inferences that can be made from mathematical models. This handbook presents a comprehensive guide to the discipline for practitioners ... Read more

    $190.00 USD

  • A First Course in Machine Learning

    by Simon Rogers, Mark Girolami ...
    Series series Chapman & Hall/CRC Machine Learning & Pattern Recognition
    "A First Course in Machine Learning by Simon Rogers and Mark Girolami is the best introductory book for ML currently available. It combines rigor and precision with accessibility, starts from a detailed explanation of the basic foundations of Bayesian analysis in the simplest of settings, and goes all the way to the frontiers of the subject such as infinite mixture models, GPs, and MCMC."—Devdatt ... Read more

    $61.99 USD

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  • Probability, Markov Chains, Queues, and Simulation

    The Mathematical Basis of Performance Modeling

    by William J. Stewart ...
    Probability, Markov Chains, Queues, and Simulation provides a modern and authoritative treatment of the mathematical processes that underlie performance modeling. The detailed explanations of mathematical derivations and numerous illustrative examples make this textbook readily accessible to graduate and advanced undergraduate students taking courses in which stochastic processes play a ... Read more

    $110.19 USD

  • Bayesian Statistics

    An Introduction

    by Peter M. Lee ...
    Bayesian Statistics is the school of thought that combines prior beliefs with the likelihood of a hypothesis to arrive at posterior beliefs. The first edition of Peter Lee’s book appeared in 1989, but the subject has moved ever onwards, with increasing emphasis on Monte Carlo based techniques.This new fourth edition looks at recent techniques such as variational methods, Bayesian importance ... Read more

    $58.00 USD

  • Elements of Information Theory

    by Thomas M. Cover, Joy A. Thomas ...
    The latest edition of this classic is updated with new problem sets and materialThe Second Edition of this fundamental textbook maintains the book's tradition of clear, thought-provoking instruction. Readers are provided once again with an instructive mix of mathematics, physics, statistics, and information theory.All the essential topics in information theory are covered in detail, including ... Read more

    $110.00 USD

  • Introduction to Bayesian Econometrics

    by Edward Greenberg ...
    This textbook explains the basic ideas of subjective probability and shows how subjective probabilities must obey the usual rules of probability to ensure coherency. It defines the likelihood function, prior distributions and posterior distributions. It explains how posterior distributions are the basis for inference and explores their basic properties. Various methods of specifying prior ... Read more

    $50.09 USD

  • Understanding Computational Bayesian Statistics

    by William M. Bolstad ...
    Series Book 644 - Wiley Series in Computational Statistics
    A hands-on introduction to computational statistics from a Bayesian point of viewProviding a solid grounding in statistics while uniquely covering the topics from a Bayesian perspective, Understanding Computational Bayesian Statistics successfully guides readers through this new, cutting-edge approach. With its hands-on treatment of the topic, the book shows how samples can be drawn from the ... Read more

    $136.00 USD

  • Probabilistic Machine Learning

    An Introduction

    by Kevin P. Murphy ...
    Series series Adaptive Computation and Machine Learning series
    A detailed and up-to-date introduction to machine learning, presented through the unifying lens of probabilistic modeling and Bayesian decision theory.This book offers a detailed and up-to-date introduction to machine learning (including deep learning) through the unifying lens of probabilistic modeling and Bayesian decision theory. The book covers mathematical background (including linear algebra ... Read more

    $77.99 USD

  • Bayesian Reasoning and Machine Learning

    by David Barber ...
    Machine learning methods extract value from vast data sets quickly and with modest resources. They are established tools in a wide range of industrial applications, including search engines, DNA sequencing, stock market analysis, and robot locomotion, and their use is spreading rapidly. People who know the methods have their choice of rewarding jobs. This hands-on text opens these opportunities to ... Read more

    $81.19 USD

  • Handbook of Monte Carlo Methods

    by Dirk P. Kroese, Thomas Taimre, Zdravko I. Botev ...
    Series Book 706 - Wiley Series in Probability and Statistics
    A comprehensive overview of Monte Carlo simulation that explores the latest topics, techniques, and real-world applicationsMore and more of today’s numerical problems found in engineering and finance are solved through Monte Carlo methods. The heightened popularity of these methods and their continuing development makes it important for researchers to have a comprehensive understanding of the ... Read more

    $154.00 USD

  • Practical Bayesian Inference

    A Primer for Physical Scientists

    by Coryn A. L. Bailer-Jones ...
    Science is fundamentally about learning from data, and doing so in the presence of uncertainty. This volume is an introduction to the major concepts of probability and statistics, and the computational tools for analysing and interpreting data. It describes the Bayesian approach, and explains how this can be used to fit and compare models in a range of problems. Topics covered include regression, ... Read more

    $45.99 USD

  • Mathematical Theory of Bayesian Statistics

    by Sumio Watanabe ...
    Mathematical Theory of Bayesian Statistics introduces the mathematical foundation of Bayesian inference which is well-known to be more accurate in many real-world problems than the maximum likelihood method. Recent research has uncovered several mathematical laws in Bayesian statistics, by which both the generalization loss and the marginal likelihood are estimated even if the posterior ... Read more

    $76.99 USD