3 papers
cs.LG2026
Spectral Disentanglement and Enhancement: A Dual-domain Contrastive Framework for Representation Learning
Jinjin Guo, Yexin Li, Zhichao Huang +5
Large-scale multimodal contrastive learning has recently achieved impressive success in learning rich and transferable representations, yet it remains fundamentally limited by the…
cs.LG2025
Graph Attention-based Adaptive Transfer Learning for Link Prediction
Huashen Lu, Wensheng Gan, Guoting Chen +2
Graph neural networks (GNNs) have brought revolutionary advancements to the field of link prediction (LP), providing powerful tools for mining potential relationships in graphs. Ho…
cs.LG2024
Core Knowledge Learning Framework for Graph Adaptation and Scalability Learning
Bowen Zhang, Zhichao Huang, Genan Dai +3
Graph classification is a pivotal challenge in machine learning, especially within the realm of graph-based data, given its importance in numerous real-world applications such as s…