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This page contains resources about Belief Networks and Bayesian Networks (directed graphical models), also called Bayes Networks.

Bayesian Networks do not necessarily follow Bayesian approach, but they are named after Bayes' Rule.

Subfields and ConceptsEdit

Online CoursesEdit

Video LecturesEdit


Lecture NotesEdit

Books and Book ChaptersEdit

  • Davidson-Pilon, C. (2015). Bayesian Methods for Hackers: Probabilistic Programming and Bayesian Inference. Addison-Wesley Professional.
  • Conrady, S., & Jouffe, L. (2015). Bayesian Networks and BayesiaLab: A Practical Introduction for Researchers. BayesiaLab USA.
  • Koduvely, H. M. (2015). Learning Bayesian Models with R. Packt Publishing.
  • Theodoridis, S. (2015). "Section 15.3: Bayesian Networks and the Markov Condition". Machine Learning: A Bayesian and Optimization Perspective. Academic Press.
  • Gelman, A., Carlin, J. B., Stern, H. S., & Rubin, D. B. (2014). Bayesian data analysis (Vol. 2). Boca Raton, FL, USA: Chapman & Hall/CRC.
  • Nagarajan, R., Scutari, M., & Lèbre, S. (2013). Bayesian Networks in R. Springer122, 125-127.
  • Barber, D. (2012). "Chapter 3: Belief Networks". Bayesian Reasoning and Machine Learning. Cambridge University Press.
  • Duda, R. O., Hart, P. E., & Stork, D. G. (2012). Pattern Classification. John Wiley & Sons.
  • Murphy, K. P. (2012). "Chapter 10: Directed graphical models (Bayes nets) ". Machine Learning: A Probabilistic Perspective. MIT Press.
  • Russell, S. J., & Norvig, P. (2010). "Part IV: Uncertain knowledge and reasoning". Artificial Intelligence: A Modern Approach. Prentice Hall.
  • Koller, D., & Friedman, N. (2009). "Chapter 3: The Bayesian Network Representation". Probabilistic Graphical Models. MIT Press.
  • Darwiche, A. (2009). Modeling and Reasoning with Bayesian Networks. Cambridge University Press.
  • Nielsen, T. D., & Jensen, F. V. (2007). Bayesian Networks and Decision Graphs. Springer Science & Business Media.
  • Bishop, C. M. (2006). "Section 8.1: Bayesian Networks". Pattern Recognition and Machine Learning. Springer.
  • Mitchell, T. M. (1997). "Chapter 6: Bayesian Learning". Machine Learning. McGraw Hill.
  • Jensen, F. (1996). An Introduction to Bayesian Networks. Springer.

Scholarly ArticlesEdit

  • Mnih, A., & Gregor, K. (2014). Neural variational inference and learning in belief networks. arXiv preprint arXiv:1402.0030.
  • Heckerman, D., Geiger, D., & Chickering, D. M. (1995). Learning Bayesian networks: The combination of knowledge and statistical data. Machine learning20(3), 197-243.

TutorialsEdit

SoftwareEdit

See Software for a complete list.

See alsoEdit

Other ResourcesEdit