Bayesian Networks
| Author | : Olivier Pourret |
| Publisher | : John Wiley & Sons |
| Total Pages | : 446 |
| Release | : 2008-04-30 |
| ISBN 10 | : 0470994541 |
| ISBN 13 | : 9780470994542 |
| Language | : EN, FR, DE, ES & NL |
Language: en
Pages: 446
Pages: 446
Bayesian Networks, the result of the convergence of artificial intelligence with statistics, are growing in popularity. Their versatility and modelling power is
Language: en
Pages: 457
Pages: 457
This is a brand new edition of an essential work on Bayesian networks and decision graphs. It is an introduction to probabilistic graphical models including Bay
Language: en
Pages: 149
Pages: 149
This publication offers and investigates efficient Monte Carlo simulation methods in order to realize a Bayesian approach to approximate learning of Bayesian ne
Language: en
Pages: 138
Pages: 138
Language: en
Pages: 128
Pages: 128
Bayesian Belief Networks are a powerful tool for combining different knowledge sources with various degrees of uncertainty in a mathematically sound and computa
Language: en
Pages: 366
Pages: 366
Bayesian Networks: An Introduction provides a self-contained introduction to the theory and applications of Bayesian networks, a topic of interest and importanc
Language: en
Pages: 322
Pages: 322
Bayesian networks currently provide one of the most rapidly growing areas of research in computer science and statistics. In compiling this volume we have broug
Language: en
Pages: 265
Pages: 265
This volume constitutes the refereed proceedings of the Second International Workshop on Advanced Methodologies for Bayesian Networks, AMBN 2015, held in Yokoha
Language: en
Pages: 328
Pages: 328
In recent years probabilistic graphical models, especially Bayesian networks and decision graphs, have experienced significant theoretical development within ar
Language: en
Pages: 662
Pages: 662
Bayesian inference networks, a synthesis of statistics and expert systems, have advanced reasoning under uncertainty in medicine, business, and social sciences.
