"A Tutorial on Learning with Bayesian Networks"

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Book	Author(s)	Year	Publisher
Learning Bayesian networks /	Neapolitan, Richard E.	[2004], ©2004.	Pearson Prentice Hall,
Bayesian Learning for Neural Networks	Radford M. Neal	1996	Springer New York
Data analysis: a Bayesian tutorial	D. S. Sivia	1996	Clarendon Press;Oxford University Press
Dynamical Systems on Networks: A Tutorial	Mason Porter; James Gleeson	1st ed. 2016	Springer International Publishing
Approximation Methods for Efficient Learning of Bayesian Networks	C. Riggelsen, C. Riggelsen	2008	IOS Press
Bayes Rule with R A Tutorial Introduction to Bayesian Analysis	James V Stone	2016	Sebtel Press
Modeling and Reasoning with Bayesian Networks	Adnan Darwiche	2009-04	Cambridge University Press
Bayesian Networks: With Examples in R	Marco Scutari; Jean-Baptiste Denis	2021	Routledge
High-Speed Networks: A Tutorial	Jorge Crichigno; Elie Kfoury; Elias Bou-Harb; Nasir Ghani	1st ed. 2022	Springer International Publishing
Doing Bayesian Data Analysis: A Tutorial Introduction with R and BUGS	John K. Kruschke, Kruschke John	2010	Academic Pr
Bayes' rule: a tutorial introduction to Bayesian analysis /	Stone, James V.,		Sebtel Press
Bayesian Networks - An Introduction	Timo Koski	2009	John Wiley & Sons
Advances in Bayesian Networks	José A. Gámez; Serafin Moral; Antonio Salmerón Cerdan	2004	Springer Berlin Heidelberg
Bayesian Networks [expert systems]	W. Premchaiswaid	2012	Intech
Risk Assessment and Decision Analysis with Bayesian Networks	Norman Fenton; Martin Neil	2018	Routledge
Bayesian Networks - A Practical Guide to Applications	Olivier Pourret	2008	John Wiley & Sons
Adaptive Learning of Polynomial Networks: Genetic Programming, Backpropagation and Bayesian Methods	Nikolay Nikolaev; Hitoshi Iba	2006	Springer US
Bayesian Networks and Decision Graphs	Thomas Dyhre Nielsen; FINN VERNER JENSEN	2001	Springer New York
Bayesian Networks and Decision Graphs	Thomas Dyhre Nielsen; FINN VERNER JENSEN	2nd ed. 2007	Springer New York
Bayesian Networks in Educational Assessment	Russell G. Almond; Robert J. Mislevy; Linda S. Steinberg; Duanli Yan; David M. Williamson	2015	Springer New York
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Chapter	Author(s)	Book	Book Authors	Year	Publisher
A Tutorial on Learning with Bayesian Networks	David Heckerman	Learning in Graphical Models	M.I. Jordan	1998	Springer Netherlands
A Tutorial on Learning with Bayesian Networks	David Heckerman	Innovations in Bayesian Networks: Theory and Applications	Dawn E. Holmes	2008	Springer Berlin Heidelberg
Learning With Bayesian Networks	David Heckerman	Machine Learning Proceedings 1995	Armand Prieditis and Stuart J. Russell	1995	Morgan Kaufmann
Learning Gene Networks with Bayesian Networks	Golan Yona	Introduction to Computational Proteomics	Golan Yona	2010	Routledge
Learning Bayesian Networks	Enrique Castillo; José Manuel Gutiérrez; Ali S. Hadi	Expert Systems and Probabilistic Network Models	Enrique Castillo; Jose M. Gutierrez; Ali S. Hadi	1997	Springer New York
Learning Bayesian Networks		Encyclopedia of Machine Learning and Data Mining	Claude Sammut; Geoffrey I. Webb	2nd ed. 2017	Springer US
Bayesian Networks: Learning	Luis Enrique Sucar	Probabilistic Graphical Models: Principles and Applications	Luis Enrique Sucar	2015	Springer London
Learning Bayesian Networks		Encyclopedia of Machine Learning	Claude Sammut; Geoffrey I. Webb	2010	Springer US
Learning Bayesian Networks	Richard E. Neapolitan; Xia Jiang	Probabilistic Methods for Financial and Marketing Informatics	Richard E. Neapolitan and Xia Jiang	2007	Morgan Kaufmann
Learning Bayesian Networks		Encyclopedia of Data Warehousing and Mining	John Wang, John Wang	2008	MIX
Bayesian Networks: Learning	Luis Enrique Sucar	Probabilistic Graphical Models: Principles and Applications	Luis Enrique Sucar	2nd ed. 2021	Springer International Publishing
A Tutorial on Bayesian Networks for Systems Health Management	Arthur Choi; Lu Zheng; Adnan Darwiche; Ole J. Mengshoel	Machine Learning and Knowledge Discovery for Engineering Systems Health Management	Ashok N. Srivastava; Jiawei Han	2012	Routledge
Learning Bayesian Networks with Local Structure	Nir Friedman; Moises Goldszmidt	Learning in Graphical Models	M.I. Jordan	1998	Springer Netherlands
A Tutorial on Optical Networks	George N. Rouskas; Harry G. Perros	Advanced Lectures on Networking: NETWORKING 2002	Enrico Gregori; Giuseppe Anastasi; Stefano Basagni	2002	Springer Berlin Heidelberg
Learning dynamic Bayesian networks	Zoubin Ghahramani	Adaptive Processing of Sequences and Data Structures: International Summer School on Neural Networks, " E. R. Caianiello" , Vietri sul Mare, Salerno, Italy, September 6-13, 1997, Tutorial Lectures	C. Lee Giles; Marco Gori	1998	Springer Berlin Heidelberg
Learning Bayesian Networks with Non-Decomposable Scores	Eunice Yuh-Jie Chen; Arthur Choi; Adnan Darwiche	Graph Structures for Knowledge Representation and Reasoning: 4th International Workshop, GKR 2015, Buenos Aires, Argentina, July 25, 2015, Revised Selected Papers	Madalina Croitoru; Pierre Marquis; Sebastian Rudolph; Gem Stapleton	1st ed. 2015	Springer International Publishing
Learning Bayesian Networks Structure with Continuous Variables	Shuang-Cheng Wang; Xiao-Lin Li; Hai-Yan Tang	Advanced Data Mining and Applications: Second International Conference, ADMA 2006, Xi' an, China, August 14-16, 2006, Proceedings	Xue Li; Osmar R. Zaiane; Zhanhuai Li	2006	Springer Berlin Heidelberg
Learning Bayesian Networks with Algebraic Differential Evolution	Marco Baioletti; Alfredo Milani; Valentino Santucci	Parallel Problem Solving from Nature – PPSN XV: 15th International Conference, Coimbra, Portugal, September 8–12, 2018, Proceedings, Part II	Anne Auger; Carlos M. Fonseca; Nuno Lourenço; Penousal Machado; Luís Paquete; Darrell Whitley	1st ed. 2018	Springer International Publishing
Learning Dynamic Bayesian Networks Structure Based on Bayesian Optimization Algorithm	Song Gao; Qinkun Xiao; Quan Pan; Qingguo Li	Advances in Neural Networks - ISNN 2007: 4th International Symposium on Neutral Networks, ISNN 2007 Nanjing, China, June 3-7, 2007. Proceedings, Part II	Derong Liu; Shumin Fei; Zengguang Hou; Huaguang Zhang; Changyin Sun	2007	Springer Berlin Heidelberg
Learning Dynamic Bayesian Networks Structure Based on Bayesian Optimization Algorit		Advances in Neural Networks – ISNN 2007: 4th International Symposium on Neural Networks, ISNN 2007, Nanjing, China, June 3-7, 2007, Proceedings, Part II	Hongwei Wang, Hong Gu (auth.), Derong Liu, Shumin Fei, Zengguang Hou, Huaguang Zhang, Changyin Sun (eds.)	2007	Springer-Verlag Berlin Heidelberg
Chapter	Author(s)	Book	Book Authors	Year	Publisher

Showing 1 to 20 of 100 entries

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