Graph Neural Networks – A Hands-On Guide to Graph Data Processing

This session introduces Graph Neural Networks (GNNs) and their innovative approach to understanding complex graphs. Dive into the core concepts—from graph representations and message passing to pooling and cutting-edge attention mechanisms. Using PyTorch Geometric, you’ll gain practical experience building, training, and optimizing GNN models on real-world datasets spanning molecular structures, social networks, and beyond.

• Date: May 14, 2025
• Time: Theory: 14:00 - 14:50 / Coffee 14:50 - 15:10 / Lab 15:10 - 16:00
• Location: Nancy-Salle A008 Jean Legras
• Instructor: Victor Pryakhin, Ph.D. Candidate
• Link to Sign-up: Sign-up here!