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
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
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…