Schedule

This is tentative course schedule, changes will be announced in the class if any and will be updated here as well.


Date Title Slides Video Extra Reading
Week 1
04-08-22 Introduction to Graph Machine Leanring + Course logistics PDF
05-08-22 Basics of Graphs PDF Tutorial-1
Week 2
11-08-22 Basics of Graphs (Traditional Graph ML) PDF Tutorial-2 Chapter-2: from GRL by W.L. Hamilton
12-08-22 Spectral Methods for Graph Clustering PDF Some Proofs
Week 3
18-08-22 Institite Foundation Day (Class Suspended)
19-08-22 Holiday
Week 4
25-08-22 Deep Learning Review : Guest Lecture (Dr. Jiaul H. Paik) PDF Chapter-3: Foundation of Deep Learning from the book DLG
26-08-22 Graph Embedding: Concurrence Preserving Methods (Introduction) PDF
Week 5
01-09-22 Graph Embedding: Structure Preserving Methods (DeepWalk and Node2vec) PDF Tutorial-3
02-09-22 Graph Embedding: Structure Preserving Methods (Struc2vec) PDF
Week 6
08-09-22 Heterogeneous Network Embedding & metapath2vec PDF
09-09-22 Graph Neural Network, Deep Graph representation: Generalized Framework PDF
Week 7
15-09-22 Neural Networks in detail: Graph Convolution Neural Network PDF
16-09-22 GNN: GraphSAGE PDF
Week 8 & Week 9
22-09-22
to
30-09-22
Mid Semester Examination
Week 10
06-10-22 Holiday
07-10-22 Knowledge Graph Embedding Will be Rescheduled
Week 11
13-10-22 Graph Attention Networks (GAT), Edge Conditioned Convolution (ECC) PDF Tutorial-4
14-10-22 Graph Pooling: Flat and Hierarchical, Downsampling, DiffPool, EigenPool PDF
Week 12
20-10-22 Heterogeneous Graph Representation Learning, Multi-Dimensional Graph Neural Networks PDF
21-10-22 Signed Graph Neural Networks PDF
Week 13
27-10-22 Knowledge Graph Embedding, Translational Distance Models, Semantic Matching Models PDF
28-10-22 Reasoning over Knowledge Graphs PDF
Week 14
03-11-22 Data Mining Applications PDF