Scalable Monte Carlo for Bayesian Learning

Discover the innovative world of Bayesian learning with Scalable Monte Carlo for Bayesian Learning by Paul Fearnhead. Published by Cambridge University Press in 2025, this hardback edition spans 247 pages of insightful content. This book offers an intuitive introduction to advanced topics in Markov chain Monte Carlo (MCMC), focusing on the latest developments that tackle the critical issue of scalability. Ideal for graduate-level courses, it serves as an essential resource for researchers and practitioners looking to deepen their understanding of MCMC techniques. Enhance your knowledge and skills in Bayesian learning with this comprehensive guide that bridges theory and application.