Graph Embedding

Spectral Graph Embedding

Thomas Bonald's lecture notes (Institut Polytechnique de Paris, 2019-2020) introduce spectral methods for graph embedding — Laplacian eigenmaps, spectral clustering, and random walk connections — grounding graph representation learning in linear algebra. These notes are foundational for understanding why GCN works and where its limitations come from.