References
The following references were used while writing this book. We encourage those of you who want to go further into the field of probabilistic graphical models and Bayesian modeling to read at least some of them.
Many of our examples and presentations of algorithms took inspiration from these books and papers.
Books on the Bayesian theory
- Gelman, A., Carlin, J.B., Stern, H.S., Dunson, D.B, Vehtari, A., and Rubin, D.B.. Bayesian Data Analysis, 3rd Edition. CRC Press. 2013. This is a reference book on Bayesian modeling covering topics from the most fundamental aspects to the most advanced, with the focus on modeling and also on computations.
- Robert, C.P.. The Bayesian Choice: From Decision-Theoretic Foundations to Computational Implementation. Springer. 2007. This is a beautiful presentation of the Bayesian paradigm with many examples. The book is more theoretical but has a rigorous presentation of many aspects of the Bayesian paradigm.
- McGrayne, Sharon Bertsch. The Theory That Would...
