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Low level scene understanding functions are formulated as various image segmentation problems, where the advantages of probabilistic inference techniques such as Markov Random Fields (MRF) or Mixed Markov Models are considered.
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The primary objective of this book is to present a comprehensive treatment of uncertainty quantification in... Læs mere
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This book provides a straightforward look at the concepts, algorithms and advantages of Bayesian Deep Learning and Deep Generative Models.
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This book provides a comprehensive coverage of the fundamentals of Bayesian inference from all important perspectives, namely theory, methods and computations. All theoretical results are presented as formal theorems, corollaries, lemmas etc., furnished with detailed proofs.
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This book provides a comprehensive coverage of the fundamentals of Bayesian inference from all important perspectives, namely theory, methods and computations. All theoretical results are presented as formal theorems, corollaries, lemmas etc., furnished with detailed proofs.
Bemærk: Kan ikke leveres før jul.
This presents recent advancements in probabilistic geotechnical site characterization. It reviews probability theories and models for... Læs mere
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In this Element, the authors introduce Bayesian probability and inference for social science students and practitioners starting from... Læs mere
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In this Element, the authors introduce Bayesian probability and inference for social science students and practitioners starting from... Læs mere
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This book offers advice on the statistical analysis of small data sets (which are often used for ethical, financial, or practical reasons) for various designs... Læs mere