Aug 24, 2024 · We propose IDOL, a novel contrastive learning framework for dynamic graph representation learning. IDOL conducts the graph propagation process.
Aug 25, 2024 · To address this challenge, we propose IDOL, a novel contrastive learning framework for dynamic graph representation learning. IDOL conducts the ...
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Jul 11, 2024 · Zhu Zulun, Nanyang Technological University.
Missing: Dynamic | Show results with:Dynamic
Code for KDD 24 paper Topology-monitorable Contrastive Learning on Dynamic Graphs. Framework. This code is implemented based on InstantGNN and GGD ...
Topology-monitorable Contrastive Learning on Dynamic Graphs Zulun Zhu, Kai Wang, Haoyu Liu, Jintang Li, Siqiang Luo*. In Proceedings of the 30th ACM SIGKDD ...
Topology-monitorable Contrastive Learning on Dynamic Graphs. Z Zhu, K Wang, H Liu, J Li, S Luo. Proceedings of the 30th ACM SIGKDD Conference on Knowledge ...
Article "Topology-monitorable Contrastive Learning on Dynamic Graphs" Detailed information of the J-GLOBAL is an information service managed by the Japan ...
Dec 19, 2024 · One of the representative paradigms is graph contrastive learning. It constructs self-supervised signals by maximizing the mutual information ...
Missing: Topology- monitorable
Topology-monitorable Contrastive Learning on Dynamic Graphs. KDD 2024: 4700 ... FastGCL: Fast Self-Supervised Learning on Graphs via Contrastive Neighborhood ...