Graph neural networks for information extraction with PyTorch

In Augusto Stoffel's talk, he introduces graph neural networks (GNNs) by comparing them to convolutional neural networks (CNNs). He describes how an image can be represented as a graph to naturally transition into the basics of GNN architecture. The talk then covers Python implementations, particularly in the PyTorch framework, and focuses on GNN applications in information extraction from tabular documents in the field of NLP.