Explores Bayesian techniques for extreme value problems, including Markov Chain Monte Carlo and Bayesian inference, emphasizing the importance of prior information and the use of graphs.
Explores verification and validation in computational modeling, emphasizing accuracy through comparison with experimental data and practical advice on model complexity.