GitHub

STM-Graph: A Python Framework for Spatio-Temporal Mapping and Graph Neural Network Predictions

STM-Graph is a Python framework for analyzing spatial-temporal urban data and doing predictions using Graph Neural Networks. It provides a complete end-to-end pipeline from raw event data to trained ...
IEEE

HGNN-GAMS: Heterogeneous Graph Neural Networks for Graph Attribute Mining and Semantic Fusion

Abstract: Heterogeneous Graph Neural Networks (HGNNs) have attracted significant research attention in recent years due to their ability to capture complex interactions among various node types in ...
Communications of the ACM

Beyond the Pipeline: A Gender Lens on Priorities and Exit Triggers in the High-Tech Industry

Among early- and mid-career computer science graduates, men are more likely than women to report no intentions to leave their ...
IEEE

Subgraph-Aware Joint Modeling for Graph Classification via Efficient Frequent Pattern Mining and Fusion

Abstract: This paper proposes a subgraph-aware classification framework that integrates efficient frequent subgraph mining with graph neural networks (GNNs) to address the limitations of existing GNNs ...