#938 overall
Monte Carlo Methods (Art Owen)
Stanford University
1 recommender · 1 thread · recommended in 1 year, 2019 · score 0.7
A Stanford course by Art Owen covering Monte Carlo methods for simulation and estimation, including variance reduction and Markov chain Monte Carlo techniques. The course materials are published on the instructor's Stanford site with a syllabus.
One commenter calls it a great course on Monte Carlo methods and points to its syllabus while arguing the field is rich and hard.
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20062026
this statement trivializes a very hard problem.
Simulating is an incredibly hard problem and MC methods and theory is an incredibly rich area of study. Some tools I use for my work in probabilistic machine learning models are MCMC techniques like HMC (Hamiltonian Monte Carlo), variance reduction techniques (Rao Blackwellization). If you would like to learn more, here is a great course: https://statweb.stanford.edu/~owen/mc/ -- you can take a look at the syllabus. Also, Casella Berger is a standard MC method book.