HCPN-GCN: Scaling Hierarchical Prototype Networks with Cone Geometry for continual graph learning
Read the original at arxiv.org→arXiv:2610.08823v1 Announce Type: new Abstract: Continual Graph Learning (CGL) aims to incrementally learn from graph-structured data while preserving knowledge acquired from previous tasks. A major challenge in...
Original headline: "HCPN-GCN: Scaling Hierarchical Prototype Networks with Cone Geometry for Continual Graph Learning"
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- Oct 8, 04:00 UTC arXiv cs.LG lead source HCPN-GCN: Scaling Hierarchical Prototype Networks with Cone Geometry for Continual Graph Learning