Introduction
This is the page of the Complex Networks course at ENS de Lyon.
This class can be followed by students from different specializations:
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, graph algorithmic, community detection, machine learning on graphs 3)An introduction to cutting-edge research topics, such as Graph embedding and Graph Convolutional Neural Networks (GCN).
Objectives
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 organisation depends on your specialization: 24h are common to all students (CS+info), 6 hours in January are mandatory only for
info students, while 6 hours of practicals are mandatory only for
CS students. All students are welcome to attend all classes if they wish.
Previous Versions
The page of last year's course can be found there:
2020/2021.