IAM761 SPECIAL TOPICS:NETWORKS AND GRAPHS
| Course Code: |
9700761 |
| METU Credit (Theoretical-Laboratory hours/week): |
3(3-0) |
| ECTS Credit: |
8.0 |
| Department: |
Institute Of Applied Mathematics |
| Language of Instruction: |
English |
| Level of Study: |
Masters |
| Course Coordinator: |
Assoc.Prof.Dr. ÖNDER TÜRK |
| Offered Semester: |
Fall or Spring Semesters. |
Course Content
This course introduces the theory and applications of Graph Neural Networks (GNNs), a class of neural networks designed for graph-structured data. It covers foundational topics in graph theory and deep learning, with a focus on GNN architectures, including Graph Convolutional Networks (GCNs), Graph Attention Networks (GATs), and other advanced models. Students will explore real-world applications of GNNs, such as social network analysis, recommendation systems, and drug discovery, and gain hands-on experience in implementing and applying GNN models.
