Worked solutions to all 342 exercises in Adnan Darwiche's Modeling and Reasoning with Bayesian Networks — propositional logic, probability calculus, building Bayesian networks, exact inference by variable elimination, factor elimination and conditioning, jointrees and graph decomposition, MPE and MAP, complexity, compilation, belief propagation, sampling, sensitivity analysis, and parameter/structure learning.
Probabilistic-Graphical-Models
2026-09-16
Adnan Darwiche’s Modeling and Reasoning with Bayesian Networks (Cambridge University Press, 2009). The COMP9418 reference text: representation (propositional logic, probability calculus, Bayesian networks), exact inference (variable elimination, factor elimination, conditioning, jointrees), advanced inference (compilation, local structure), approximate inference (belief propagation, sampling), and learning (maximum likelihood and Bayesian).
Worked solutions to all 342 exercises live at Solutions to Darwiche’s Modeling and Reasoning with Bayesian Networks.