Graph neural networks

May 25, 2026

Graph Neural Networks Explained: A Clear Guide to GNN Basics & Models

An introduction to Graph Neural Networks (GNNs), covering fundamental concepts like nodes, edges, and embeddings. This post delves into the core message-passing mechanism and provides a detailed overview of key architectures including GCN, GraphSAGE, GAT, GIN, and Graph Transformers, explaining their unique approaches and mathematical formulations.

Jan 16, 2026

Graph Neural Networks Just Solved Enterprise AI?

Jure Leskovec introduces Relational Foundation Models (RFMs), a new class of models based on graph neural networks that learn directly from raw, multi-table enterprise data. This approach bypasses manual feature engineering, leading to more accurate, faster-to-deploy, and easier-to-maintain predictive models for tasks like churn prediction, fraud detection, and recommendation systems.