Concept
Échantillonnage préférentiel
Cours associés (6)
MATH-414: Stochastic simulation
The student who follows this course will get acquainted with computational tools used to analyze systems with uncertainty arising in engineering, physics, chemistry, and economics. Focus will be on s
PHYS-403: Computer simulation of physical systems I
The two main topics covered by this course are classical molecular dynamics and the Monte Carlo method.
MSE-639: Statistical methods in atomistic computer simulations
The course gives an overview of atomistic simulation methods, combining theoretical lectures and hands-on sessions. It
covers the basics (molecular dynamics and monte carlo sampling) and also more adv
PHYS-467: Machine learning for physicists
Machine learning and data analysis are becoming increasingly central in sciences including physics. In this course, fundamental principles and methods of machine learning will be introduced and practi
COM-516: Markov chains and algorithmic applications
The study of random walks finds many applications in computer science and communications. The goal of the course is to get familiar with the theory of random walks, and to get an overview of some appl
MATH-435: Bayesian Computation
This course aims at giving a broad overview of Bayesian inference, highlighting how the basic Bayesian paradigm proceeds, and the various methods that can be used to deal with the computational issues