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Books on the topic 'Probabilistic Bayesian Network'

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1

Lim, Chee Peng. Probabilistic fuzzy ARTMAP: An autonomous neural network architecture for Bayesian probability estimation. University of Sheffield, Dept. of Automatic Control & Systems Engineering, 1995.

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2

A, Gammerman, and UNICOM Seminars, eds. Probabilistic reasoning and Bayesian belief networks. Alfred Waller in association with UNICOM, 1995.

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3

Taroni, Franco, Colin Aitken, Paolo Garbolino, and Alex Biedermann. Bayesian Networks and Probabilistic Inference in Forensic Science. John Wiley & Sons, Ltd, 2006. http://dx.doi.org/10.1002/0470091754.

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4

Taroni, Franco, Alex Biedermann, Silvia Bozza, Paolo Garbolino, and Colin Aitken. Bayesian Networks for Probabilistic Inference and Decision Analysis in Forensic Science. John Wiley & Sons, Ltd, 2014. http://dx.doi.org/10.1002/9781118914762.

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5

1955-, Lucas Peter, Gámez José A, and Salmerón Antonio, eds. Advances in probabilistic graphical models. Springer, 2007.

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6

Taroni, Franco, Colin Aitken, Paolo Garbolino, and Alex Biedermann. Bayesian Networks and Probabilistic Inference in Forensic Science. Wiley & Sons, Limited, John, 2006.

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7

Cowell, Robert G., David J. Spiegelhalter, Steffen L. Lauritzen, and Philip Dawid. Probabilistic Networks and Expert Systems: Exact Computational Methods for Bayesian Networks. Springer London, Limited, 2006.

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8

Probabilistic methods for bionformatics: With an introduction to Bayesian networks. Morgan Kaufmann Publishers, 2009.

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9

Probabilistic Reasoning and Bayesian Belief Networks (UNICOM - Information & Communications Technology). Nelson Thornes Ltd, 1998.

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10

Neapolitan, Richard E. Probabilistic Methods for Bioinformatics: With an Introduction to Bayesian Networks. Elsevier Science & Technology Books, 2009.

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11

(Editor), Alexander Gammerman, J. G. Taylor (Editor), and V. Rayward-Smith (Editor), eds. Probabilistic Reasoning and Bayesian Belief Networks / Neural Networks / Applications of Modern Heuristic Methods. Alfred Waller, 1994.

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12

Taroni, Franco, Colin Aitken, Paolo Garbolino, Alex Biedermann, and Silvia Bozza. Bayesian Networks for Probabilistic Inference and Decision Analysis in Forensic Science. Wiley & Sons, Incorporated, John, 2014.

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13

Taroni, Franco, Colin Aitken, Paolo Garbolino, Alex Biedermann, and Silvia Bozza. Bayesian Networks for Probabilistic Inference and Decision Analysis in Forensic Science. Wiley & Sons, Incorporated, John, 2014.

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14

Taroni, Franco, Colin Aitken, Paolo Garbolino, and Alex Biedermann. Bayesian Networks and Probabilistic Inference in Forensic Science (Statistics in Practice). Wiley, 2006.

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15

Taroni, Franco, Colin Aitken, Paolo Garbolino, Alex Biedermann, and Silvia Bozza. Bayesian Networks for Probabilistic Inference and Decision Analysis in Forensic Science. Wiley & Sons, Limited, John, 2014.

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16

Bayraktarli, Yahya Yilmaz. Construction and Application of Bayesian Probabilistic Networks for Earthquake Risk Management. vdf Hochschulverlag ETH Zurich, 2011.

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17

Lucas, Peter, José A. Gámez, and Antonio Salmerón Cerdan. Advances in Probabilistic Graphical Models. Springer London, Limited, 2007.

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18

Lucas, Peter, José A. Gámez, Various, and Antonio Salmerón Cerdan. Advances in Probabilistic Graphical Models. Springer, 2010.

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19

Cowell, Robert G., David J. Spiegelhalter, A. Philip Dawid, and Steffen L. Lauritzen. Probabilistic Networks and Expert Systems: Exact Computational Methods for Bayesian Networks (Information Science and Statistics). Springer, 2007.

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20

Bayesian Networks for Probabilistic Inference and Decision Analysis in Forensic Science 2e Statistics in Practice. John Wiley and Sons Ltd, 2014.

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21

(Editor), Peter Lucas, José A. Gámez (Editor), and Antonio Salmerón (Editor), eds. Advances in Probabilistic Graphical Models (Studies in Fuzziness and Soft Computing). Springer, 2007.

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22

A Discriminative Approach to Bayesian Filtering with Applications to Human Neural Decoding. Brown University, 2019.

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23

Trappenberg, Thomas P. Fundamentals of Machine Learning. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198828044.001.0001.

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Machine learning is exploding, both in research and for industrial applications. This book aims to be a brief introduction to this area given the importance of this topic in many disciplines, from sciences to engineering, and even for its broader impact on our society. This book tries to contribute with a style that keeps a balance between brevity of explanations, the rigor of mathematical arguments, and outlining principle ideas. At the same time, this book tries to give some comprehensive overview of a variety of methods to see their relation on specialization within this area. This includes
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24

Mungoli, Neelesh. Advanced Probabilistic Graphical Models in Machine Learning : a Comprehensive Treatise on Bayesian Networks, Markov Chains, and Beyond : Mastering the Art of Uncertainty: Techniques, Algorithms, and Real-World Applications for Complex Decision-Making and Prediction. Absolute Author Publishing House, 2023.

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