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What is Bayesian Network Inference Methods about?

- Bayesian networks use inference algorithms like enumeration, variable elimination, and belief propagation to calculate the posterior probability of a variable conditioned on evidence by marginalizing over unobserved variables. - Approximate inference methods like sampling generate a set of samples representing possible joint variable assignments to estimate conditional probabilities. Gibbs sampling iteratively resamples each variable conditioned on its neighbors to converge to the joint probability distr

Author

Vaijayanthi S

Language

EN