Concept
Topologie de réseau
Cours associés (31)
CS-721: Privacy at the communication layer
In this seminar course students will get in depth understanding of mechanisms for private communication. This will be done by reading important papers that will be analyzed in the class. Students will
MATH-681: Reading group in applied topology II
In this reading group, we will work together through recent important papers in applied topology.
Participants will take turns presenting articles, then leading a discussion of the contents.
ME-427: Networked control systems
This course offers an introduction to control systems using communication networks for interfacing sensors, actuators, controllers, and processes. Challenges due to network non-idealities and opportun
AR-219: Advanced CAO and Integrated Modeling DIM
1ère année: bases nécessaires à la représentation informatique 2D (3D).
Passage d'un à plusieurs logiciels: compétence de choisir les outils adéquats en 2D et en 3D.
Mise en relation des outils de CAO
MATH-448: Statistical analysis of network data
A first course in statistical network analysis and applications.
EE-370: Electric power systems
Ce cours décrit les composants d'un réseau électrique. Il explique le fonctionnement des réseaux électriques et leurs limites d'utilisation. Il introduit les outils de base permettant de les piloter.
PHYS-316: Statistical physics II
Introduction à la théorie des transitions de phase
NX-450: Computational neurosciences: biophysics
The course introduces students to a synthesis of modern neuroscience and state-of-the-art data management, modelling and computing technologies with a focus on the biophysical level.
CS-451: Distributed algorithms
Computing is nowadays distributed over several machines, in a local IP-like network, a cloud or a P2P network. Failures are common and computations need to proceed despite partial failures of machin
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