Text classification is a critical task for understanding the knowledge behind text, especially in medical text. In this paper, we propose a medical graph diffusion model, named the MGD model, for the ...

Diffusion processes, characterised through operators such as the graph Laplacian, foster the development of diffusion maps which yield robust, multi-scale representations.

In this work, we present Stochastic Graph Neural Diffusion, which approaches deep learning on graphs as a continuous stochastic heat diffusion process. We generalize the Stochastic Heat Equation on ...

This repository contains the source code for the paper "Fine-scale striatal parcellation using diffusion MRI tractography and graph neural networks." The code leverages graph neural networks (GNNs) to ...

Overview This project uses graph neural networks (GNNs) to perform fine-scale parcellation of the striatum based on diffusion MRI tractography data. It consists of two main stages: Pretraining A GCN ...