Graph generation is a complex problem that involves constructing structured, non-Euclidean representations while maintaining meaningful relationships between entities. Most current methods fail to ...

This is the repository for the implementation of the models and the experiments described in the paper "Learning Individual Behavior in Agent-Based Models with Graph Diffusion Networks". Graph ...

Computes Mean Squared Error (MSE) between clean and denoised coordinates. Visualizes graphs (clean, noisy, and denoised) with side-by-side comparison. Clean Graph ...

Graph-based manifold learning and diffusion processes provide a powerful framework for extracting intrinsic geometric features from high-dimensional data. By constructing a graph where nodes represent ...

Abstract: Despite advancements using graph neural networks (GNNs) to capture complex user-item interactions, challenges persist due to data sparsity and noise. To address these, self-supervised ...

With the rapid development of modern Chinese medicine prescription recommendation technology based on artificial intelligence technology, the existing herb recommendation model lacks attention to the ...