Graph neural networks (GNNs) have emerged as a powerful framework for analyzing and learning from structured data represented as graphs. GNNs operate directly on graphs, as opposed to conventional ...

Jack Newcomb, a student studying Physics, used neural networks to classify waveforms. Neural networks are computer systems modeled after the human brain to identify patterns. Newcomb’s project focused ...

Graph out-of-distribution (OOD) generalization remains a major challenge in graph neural networks (GNNs). Invariant learning, aiming to extract invariant features across varied distributions, has ...