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This book brings the power of modern Bayesian thinking, modeling, and computing to a broad audience. In particular, it is an ideal resource for... Læs mere
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The course covers the fundamental philosophy and principles of Bayesian inference, including the reasoning behind the prior/likelihood model... Læs mere
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This book gets you up and running with doing complex Bayesian statistics, focussing on applied analysis rather than maths.
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This open access book focuses on robot introspection, which has a direct impact on physical human–robot interaction and long-term autonomy, and which can benefit from autonomous anomaly monitoring and diagnosis, as well as anomaly recovery strategies.
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The book introduces Bayesian networks using simple yet meaningful examples. Discrete Bayesian networks are described first followed by Gaussian Bayesian networks and mixed networks. All steps in learning are illustrated with R code.
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"An advanced-level textbook on Bayesian statisitics primarily aimed at students in the cognitive, behavioral, and social sciences"--
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Designed for researchers and graduate students in machine learning, this book introduces the theory of variational Bayesian learning, a popular machine learning... Læs mere
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The Handbook of ABC provides illuminating insight into the world of Bayesian modelling for intractable models for both experts and newcomers alike. It is an... Læs mere
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Spatial and Spatio-Temporal Bayesian Models with R-INLA provides a much needed, practically oriented & innovative presentation of the combination of Bayesian methodology and spatial statistics.
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