This is the page of the Complex Networks course, part of the Science of Complex Systems Option
of the M2 at ENS de Lyon.
The class will cover: 1)Fundamentals of Network Science, e.g., Classic random models, centralities, small-world phenomenon, etc. 2)Focus classes on advances topics, e.g., dynamic networks, community detection, machine learning on graphs 3)An introduction to cutting-edge research topics, such as Graph embedding and Graph Convolutional Neural Networks (GCN).
This class is thought to provide a broad overview of current topics in network science. It is grouded in research, with short presentations by researchers in the field introducing their research questions, and a cession for collective reading and commenting of recent scientific articles. The objective of the course is to lead the students to a point where they are able to gain a general understanding of most articles currently published in the field.
Overview of the course
The course is composed of 24h of lectures, and 6 hours of tutorial (TP).
Lectures will take place every Thursday at 10:15 a.m in amphi H. (Exceptionnaly the first lecture (September 12) will start at 10:45).
The content of the class this year is new, but based in part on the course of the previous lecturer
, Marton Karsai, in part on a previous lecture
by myself, and in part on new contents.