CORE: New Contrastive Learning Method for Graph Feature Reconstruction

This article introduces CORE, a novel method for contrastive learning on graphs, which is a key area of research in machine learning. While the specifics of the method are not detailed, the focus on graph-based feature reconstruction suggests potential applications in diverse domains.

• •CORE focuses on contrastive masked feature reconstruction on graphs.
• •The method is likely related to graph neural networks.
• •The research paper is available on ArXiv, suggesting early-stage findings.