2 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.LG2025
A Scalable Pretraining Framework for Link Prediction with Efficient Adaptation
Yu Song, Zhigang Hua, Harry Shomer +4
Link Prediction (LP) is a critical task in graph machine learning. While Graph Neural Networks (GNNs) have significantly advanced LP performance recently, existing methods face key…
cs.LG2024★ 2 cited
Mixture of Link Predictors on Graphs
Li Ma, Haoyu Han, Juanhui Li +4
Link prediction, which aims to forecast unseen connections in graphs, is a fundamental task in graph machine learning. Heuristic methods, leveraging a range of different pairwise m…
cs.LG2023★ 1 cited
Spectral-Aware Augmentation for Enhanced Graph Representation Learning
Kaiqi Yang, Haoyu Han, Wei Jin +1
Graph Contrastive Learning (GCL) has demonstrated remarkable effectiveness in learning representations on graphs in recent years. To generate ideal augmentation views, the augmenta…