Recursos biliográficos

[1] D. Koller and N. Friedman, Probabilistic Graphical Models: Principles and Techniques. Cambridge, MA: MIT Press, 2009.

[2] C. M. Bishop, Pattern Recognition and Machine Learning. Springer, 2006. [Online]. Available: https://www.microsoft.com/en-us/research/publication/pattern-recognition-machine-learning

[3] K. P. Tran, Ed., Machine Learning and Probabilistic Graphical Models for Decision Support Systems, st ed. Boca Raton, FL, USA: CRC Press, 2022. Available: https://doi.org/10.1201/9781003189886

[4] D. Barber, Bayesian Reasoning and Machine Learning. Cambridge University Press, 2012.

[5] R. McElreath, Statistical Rethinking: A Bayesian Course with Examples in R and Stan, 2nd ed. Boca Raton, FL: CRC Press, 2018.

[6] O. A. Martin, R. Kumar, and J. Lao, Bayesian Modeling and Computation in Python. Boca Raton, FL: CRC Press, 2021. [Online]. Available: https://bayesiancomputationbook.com/welcome.html

[7] I. Fornacon-Wood et al., «Understanding the Differences Between Bayesian and Frequentist Statistics,» Int. J. Radiat. Oncol. Biol. Phys., vol. 112, no. 5, pp. 1076–1082, 2022. [Online]. Available: https://www.redjournal.org/article/S0360-3016(21)03256-9/fulltext