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 covers: 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, collective reading and commenting of recent scientific articles, and experimental applications of key concepts. 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).
The page of last year's course can be found there: 2019/2020
Before that, the instructor was Marton Karsai and its course can be found there