Overview: A Monte Carlo textbook suitable for students and researchers in the areas of computer vision, machine learning, robotics, artificial intelligence, graphics, etc.An easy to understand textbook featurin.This book seeks to bridge the gap between statistics and computer science. It provides an overview of Monte Carlo methods, including Sequential Monte Carlo, Markov Chain Monte Carlo, Metropolis-Hastings, Gibbs Sampler, Cluster Sampling, Data Driven MCMC, Stochastic Gradient descent, Langevin Monte Carlo, Hamiltonian Monte Carlo, and energy landscape mapping. Due to its comprehensive nat
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