5 papers
OpenGLT: A Comprehensive Benchmark of Graph Neural Networks for Graph-Level Tasks
Haoyang Li, Yuming Xu, Alexander Zhou +4
Graphs are fundamental data structures for modeling complex interactions in domains such as social networks, molecular structures, and biological systems. Graph-level tasks, which…
Counting Balanced Triangles on Social Networks With Uncertain Edge Signs
Alexander Zhou, Haoyang Li, Anxin Tian +2
On signed social networks, balanced and unbalanced triangles are a critical motif due to their role as the foundations of Structural Balance Theory. The uses for these motifs have…
GPU-Accelerated Algorithms for Graph Vector Search: Taxonomy, Empirical Study, and Research Directions
Yaowen Liu, Xuejia Chen, Anxin Tian +7
Approximate Nearest Neighbor Search (ANNS) underpins many large-scale data mining and machine learning applications, with efficient retrieval increasingly hinging on GPU accelerati…
Epidemiology-informed Graph Neural Network for Heterogeneity-aware Epidemic Forecasting
Yufan Zheng, Wei Jiang, Tong Chen +4
Among various spatio-temporal prediction tasks, epidemic forecasting plays a critical role in public health management. Recent studies have demonstrated the strong potential of spa…
UniCom: Towards a Unified and Cohesiveness-aware Framework for Community Search and Detection
Yifan Zhu, Hanchen Wang, Wenjie Zhang +2
Searching and detecting communities in real-world graphs underpins a wide range of applications. Despite the success achieved, current learning-based solutions regard community sea…