1 |
Feb 17th |
Course motivation, graph theory vs network science, graphology |
Recitation on NetworkX library, Pajek format etc. |
|
2 |
Feb 24th |
/ (illness) |
/ (illness) |
|
3 |
Mar 3rd |
Networkology, network representations & data, Erdos-Renyi model |
Network representations, basic network algorithms |
Homework #1 out |
4 |
Mar 10th |
Configuration model, small-world networks & model, scale-free structure |
Advanced network algorithms, random graph models |
|
5 |
Mar 17th |
Scale-free networks & preferential attachment models, course projects |
Small-world & scale-free models, graphs vs networks |
|
6 |
Mar 24th |
Node position & measures of centrality, link analysis algorithms |
Measures of node centrality, PageRank algorithm |
|
7 |
Mar 31st |
Link importance & measures of bridging, networks in science, community structure |
Node similarity, link betweenness, errors & attacks |
Homework #1 due |
8 |
Apr 7th |
Community detection & graph partitioning, node equivalence & blockmodeling |
Community structure & detection, benchmark graphs |
Homework #2 out |
9 |
Apr 14th |
Core-periphery structure, node mixing, motifs & graphlets |
Blockmodeling & block models, \(k\)-core network decomposition |
|
10 |
Apr 21st |
/ (holiday) |
Node mixing by (not) degree, graphlet degrees |
|
11 |
Apr 28th |
Network sampling & comparison, backbones & (convex) skeletons |
Random-walk sampling, network comparison measures |
|
12 |
May 5th |
Node layout & network visualization, selected applications |
Board with pegs & bands, wiring diagrams, block models |
Homework #2 due |
13 |
May 12th |
Network inference & link prediction indices, graph machine learning |
Node embeddings & classification, link prediction |
|
14 |
May 19th |
Selected applications & research topics, course challenges |
Selected analyses, review & examples of final exam |
|
15 |
May 26th |
Course wrap-up, invited talk on network dynamics (Andreas Kaltenbrunner) |
/ (consultations) |
|
16 |
Jun 2nd |
/ (NetSci ‘25) |
/ (NetSci '25) |
Course project due |