

High-dimentional classification with deep neural networks: decision boundaries, noise, and margin
By Philipp Petersen


New dynamical low-complexity approximations for the Schrödinger equation
By Virginie Ehrlacher
By Giray Ökten
Appears in collection : Jean-Morlet Chair 2020 - Research School: Quasi-Monte Carlo Methods and Applications / Chaire Jean-Morlet 2020 - Ecole: Méthode de quasi-Monte-Carlo et applications
The models of Bachelier and Samuelson will be introduced. Methods for generating number sequences from non-uniform distributions, such as inverse transformation and acceptance rejection, as well as generation of stochastic processes will be discussed. Applications to pricing options via rendomized quasi-Monte Carlo methods will be presented.