The subgraphs for training are preprocessed with motif detection and stored in different files in this code. We provide StackOverflow as an example. The 1h scale can be used directly, while the 5h and ...

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. Innovative drugs represent a critical approach to addressing ...

Google published details of a new kind of AI based on graphs called a Graph Foundation Model (GFM) that generalizes to previously unseen graphs and delivers a three to forty times boost in precision ...

Abstract: 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 ...

Stroke remains a leading cause of mortality and disability worldwide, requiring timely therapeutic decisions. Existing content-based drug recommendation approaches often rely on static similarity ...

Abstract: Network planning is crucial to facilitate network service under limited network operation costs. However, adapting the network topology (i.e., connections and capacities for physical and IP ...

This will print training stats, compute Valid Path Rate on a test split, and pop up a NetworkX plot with one predicted sample. Tip: If you just want a tiny smoke test, run python sanity.py. main.py # ...

Multimodal Attributed Graphs (MMAGs) have received little attention despite their versatility in image generation. MMAGs represent relationships between entities with combinatorial complexity in a ...