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 ...

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This paper proposes a river network feature identification architecture based on coupled dynamic partial differential diffusion equations and graph neural networks. By deeply analyzing the solving ...

Graph Diffusion Network (GDN) is a framework that combines a graph neural network with a diffusion model to learn a differentiable surrogate of an ABM, from ABM-generated data. In this framework, a ...

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

InstructG2I was tested on three datasets from different domains – ART500K, Amazon, and Goodreads. For text-to-image methods, Stable Diffusion 1.5 was decided as the baseline model, and for ...