Covers maximum likelihood estimation to estimate parameters by maximizing prediction accuracy, demonstrating through a simple example and discussing validity through hypothesis testing.
Explores computing density of states and Bayesian inference using importance sampling, showcasing lower variance and parallelizability of the proposed method.
