Introduction to Graph Neural Networks
Chapter 1: Foundations of Graph-Based Learning
What is Graph Data?
Limitations of Standard Neural Networks on Graphs
Common Graph Machine Learning Tasks
Representing Graphs: Adjacency and Feature Matrices
Graph Properties and Measurements
Introduction to the NetworkX Library
Hands-on: Loading and Inspecting a Graph Dataset
Chapter 2: The Message Passing Mechanism
The Neighborhood Aggregation Idea
A General GNN Layer: Aggregate and Update
Common Aggregation Functions
Update Functions and Non-Linearities
Permutation Invariance and Equivariance
Stacking Layers to Form a Deep GNN
Practice: A Simple GNN Layer with NumPy
Chapter 3: Foundational GNN Architectures
Graph Convolutional Networks (GCN)
A Spatial Interpretation of Graph Convolutions
GraphSAGE: Sampling and Aggregating Neighborhoods
Inductive Learning with GraphSAGE
Graph Attention Networks (GAT)
The Attention Mechanism in GATs
Comparing GCN, GraphSAGE, and GAT
Hands-on: Implementing a GCN from Scratch
Chapter 4: Training GNN Models
Setting up a GNN for Node Classification
Loss Functions for Graph Tasks
The Training Loop for GNNs
Data Splitting in Graphs: Transductive vs. Inductive
Evaluation Metrics for Node Classification
Overfitting and Regularization in GNNs
Practice: Training and Evaluating your GCN
Chapter 5: GNN Implementation with PyTorch Geometric
Introduction to PyTorch Geometric (PyG)
The PyG Data Object
Working with PyG Datasets
Building Models with PyG GNN Layers
Mini-Batching for Large Graphs
A Complete Training Script in PyG
Hands-on: Node Classification on the Cora Dataset with PyG
Hands-on: Loading and Inspecting a Graph Dataset
Was this section helpful?
- NetworkX Documentation, NetworkX Developers, 2024 - Official documentation for the NetworkX Python library, detailing graph creation, manipulation, analysis, and visualization functions.
- An Information Flow Model for Conflict and Fission in Small Groups, Wayne W. Zachary, 1977 Journal of Anthropological Research, Vol. 33 (University of New Mexico) DOI: 10.1086/jar.33.4.3629752 - The original research paper introducing the Zachary's Karate Club dataset, describing the social network and the observed club split.
- Networks: An Introduction, Mark E. J. Newman, 2018 (Oxford University Press) DOI: 10.1093/oso/9780198805090.001.0001 - A comprehensive textbook on network science, covering graph theory, network properties, and matrix representations relevant for graph datasets.
- Graph Neural Networks: Foundations, Frontiers, and Applications, Lingfei Wu, Peng Cui, Jian Pei, Liang Zhao, 2022 (Springer Nature) DOI: 10.1007/978-981-16-6054-2 - A textbook offering a broad overview of Graph Neural Networks, explaining graph representations and data structures in the context of GNNs.