Lecture

Monte Carlo Methods: Metropolis Algorithm

Description

This lecture covers the concepts of Monte Carlo methods, importance sampling, and the Metropolis algorithm. Importance sampling is explained through interactions between nearest neighbors and mean value calculations. The Metropolis algorithm is detailed, including the detailed balance condition and practical implementation in a cement simulation.

In MOOC

Instructor

esse ea

Esse ad occaecat aliquip dolore labore exercitation minim laboris. In fugiat laboris est minim veniam sit pariatur nisi proident nulla quis deserunt in non. Proident aliqua minim qui enim ad irure aliquip. Magna laboris cupidatat qui nostrud veniam adipisicing. Pariatur deserunt id consectetur quis velit ipsum voluptate. Enim ut occaecat adipisicing sint anim dolore tempor incididunt irure consectetur.

Official source

https://mediaspace.epfl.ch/media/0_ru5ftxty

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Related lectures (32)

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.