Unit 1: Introduction to Edge Representation Learning
Unit 2: Core Concepts of Graph Neural Networks
Unit 3: Implementing Basic GNNs for Node and Graph Classification
Advanced Edge Representation Learning with GNNs
Master advanced techniques in edge representation learning using Graph Neural Networks (GNNs) to unlock powerful insights from graph data for real-world applications.
Unit 1: Introduction to Specialized GNNs for Edges
Unit 2: Implementing EdgeConv
Unit 3: Edge Feature Engineering
Unit 4: Integrating Edge Features into GNN Models
Unit 1: Attention Mechanisms for Edges
Unit 2: Hierarchical Graph Representation
Unit 3: Dynamic Graphs and Temporal GNNs
Unit 1: Applications of Edge Representation Learning
Unit 2: Evaluation Metrics and Benchmarks