Home Events Calendar StudON: Crash Course in Monte Carlo methods (1st session)

StudON: Crash Course in Monte Carlo methods (1st session)

FAU – Friedrich Alexander Universität Erlangen-Nürnberg organizes the course the e-learning platform StudON: Crash Course in Monte Carlo methods, by Philipp Konstantin Wacker in two sessions:

  • 1st session on May 22nd, 2020
  • 2d session TBD (soon)

 

To whom? Anyone who always wanted to learn how to do computations randomly. and not yet familiar with Monte Carlo methods. Basic knowledge about random variables are required (i.e. what is a probability distribution function, what is the expectation of a random variable, how do we transform random variables, what is Bayes’ law etc.).

Access. Public

Joining the course StudON link via Zoom 

[Session 1] convers Bayesian inverse problems (this will be our framework under which we think about Monte Carlo methods), the idea of sampling, how we can compute integrals with them, importance sampling and rejection sampling.

[Session 2] Markov Chain Monte Carlo methods, which is a quite successful and modern way of doing Monte Carlo.

There will be some kind of practical session after that so we can apply what we’ve learned to an interesting problem.

This will be a crash course aimed at anyone who is not yet familiar with Monte Carlo methods, this means no advanced topics like geometric ergodicity, sampling in infinite dimensions, spectral gaps etc. are covered. This course is supposed to give you enough intuition so you know what Monte Carlos is basically about and you could pick up more advanced books or papers to learn more. It will also enable you to casually drop The Secret Acronyms (MH-MCMC, gpCN, MALA,…) in conversation.

The event is finished.

Date

Time

1:00 pm - 3:00 pm

Local Time

  • Timezone: America/New_York
  • Date: Wed 12th Aug 2020
  • Time: 6:00 pm - 6:00 pm

More Info

Joining to Zoom

Labels

Course
FAU - Erlangen-Nürnberg

Organizer

FAU - Erlangen-Nürnberg
Website
https://en.www.math.fau.de/
Joining to Zoom