PHYS-432: Quantum field theory IIThe goal of the course is to introduce relativistic quantum field theory as the conceptual and mathematical framework describing fundamental interactions such as Quantum Electrodynamics. ...
CS-438: Decentralized systems engineeringA decentralized system is one that works when no single party is in charge or fully trusted. This course teaches decentralized systems principles while guiding students through the engineering of their own decentralized system featuring messaging, file sha ...
CS-250: Algorithms IThe students learn the theory and practice of basic concepts and techniques in algorithms. The course covers mathematical induction, techniques for analyzing algorithms, elementary data structures, major algorithmic paradigms such as dynamic programming, s ...
MATH-487: Introduction to multi-scale stochastic dynamicsThis course introduces slow/fast systems and the mathematical tools used to derive effective equations governing their behaviour. Students will learn core concepts and techniques for rigorously analysing complex stochastic multi-scale systems. ...
MATH-240: StatistiqueCe cours donne une introduction au traitement mathématique de la théorie de l'inférence statistique en utilisant la notion de vraisemblance comme un thème central. ...
MATH-442: Statistical theoryThis course gives a mostly rigourous treatment of some statistical methods outside the context of standard likelihood theory. ...
ME-716: Similarity and Transport Phenomena in FluidThe course is an introduction to symmetry analysis in fluid mechanics. The student will learn how to find similarity and travelling-wave solutions to partial differential equations used in fluid and continuum mechanics. The course covers mathematical and p ...
MATH-522: Empirical processesWe learn how to control the nonasymptotic and random behavior of collections of estimators, when indexed by classes of functions/sets. Examples range from prototypical estimators used by statisticians, to nonparametric models used in machine learning. ...
CS-459: Foundations of probabilistic proofsProbabilistic proof systems (eg PCPs and IPs) have had a tremendous impact on theoretical computer science, as well as on real-world secure systems. They underlie delegation of computation protocols and hardness of approximation. This course covers the fou ...
MATH-301: Equations différentielles ordinairesCe cours donne une introduction rigoureuse au principaux thèmes de la théorie des équations différentielles ordinaires (EDO). Les EDO sont fondamentales pour l'étude des systèmes dynamiques et des équations aux dérivées partielles. Des applications dans ce ...
MATH-101(de): Analyse I (allemand)Es werden die Grundlagen der Analysis sowie der Differential- und Integralrechnung von Funktionen einer reellen Veränderlichen erarbeitet. ...
MATH-664: Malliavin calculus and normal approximationsThis course will provide a basic knowledge of the stochastic calculus of variations with respect to the Brownian motion. A variety of applications will be presented including the regularity of probability densities and quantitative normal approximations. ...
MATH-685: Learning Theory of Nonparametric RegressionThis course is intended to give a brief overview of how to prove consistency results in nonparametric regression. In particular, we will focus on least-square regression estimators. Some connections to the empirical risk minimization (ERM) problem will be ...
CS-602: Foundation of probabilistic proofsProbabilistic proof system (eg PCPs and IPs) have had a tremendous impact on the theoretical computer science, and have also found practical uses. They underlie delegation of computation protocols and hardness of approximation. This course covers the found ...
