Abstract: Heterogeneous Graph Neural Networks (HGNNs) aim to embed rich structural and semantic information of heterogeneous graphs into low-dimensional node representations. While HGNNs extend the ...

Abstract: Sequence-to-graph alignment is a critical component of pan-genome-based read alignment and represents the most computationally intensive step in this process. To address this challenge, we ...