Handbook Of Markov Chain Monte Carlo -
: Coverage of integrating MCMC with deep learning and machine learning approaches, along with guidance for implementation on modern hardware.
A revised second edition, featuring new editors and Dootika Vats , reflects the rapid evolution of the field since 2011: Handbook of Markov Chain Monte Carlo
The is a definitive reference for developers and practitioners in the field of statistical computing. Edited by a "world-class" team including Steve Brooks , Andrew Gelman , Galin Jones , and Xiao-Li Meng , it serves as a successor to earlier foundational texts, providing a modern, comprehensive look at MCMC technology. Core Structure and Content : Coverage of integrating MCMC with deep learning









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