The first part is devoted to Monge and Kantorovitch problems, discussing the existence and the properties of the optimal plan. The second part introduces the Wasserstein distance on measures and develops applications of optimal transport to PDEs, functiona ...
This course presents the problem of static optimization, with and without (equality and inequality) constraints, both from the theoretical (optimality conditions) and methodological (algorithms) point of view. Economics and financial applications are provi ...
The goal of this course is to instruct the student how fundamental scientific knowledge, acquired through the study of fundamental disciplines, including biochemistry, genetics, pharmacology, physiology, genomics, cell and molecular biology can be applied ...
This course is intended for students who want to understand modern large-scale data analysis systems and database systems. It covers a wide range of topics and technologies, and will prepare students to be able to build such systems as well as read and und ...
"In silico Neuroscience" introduces students to a synthesis of modern neuroscience and state-of-the-art data management, modelling and computing technologies. ...
Introduction to systems engineering using the classical V-model. Topics include stakeholder analysis, requirements definition, concept selection, design definition and optimization, system integration and verification and validation. This class is part of ...
Le but du cours est de transmettre aux étudiants les concepts, les méthodes et les algorithmes de base de la conception de produit en rapport avec son cycle de vie. ...