From Priors to Predictions: Explaining and Visualizing Human Reasoning in a Graph Neural Network Framework

This article likely presents a research paper exploring the use of Graph Neural Networks (GNNs) to model and understand human reasoning processes. The focus is on explaining and visualizing how these networks arrive at their predictions, potentially by incorporating prior knowledge. The use of GNNs suggests a focus on relational data and the ability to capture complex dependencies.