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20222026
most citedA survey of dynamic graph neural networks

2 citations · 5 across the 8 of their papers we have counts for

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Showing cs.LGShow all

7 papers · 1 filter

cs.LG2025

Lighter-X: An Efficient and Plug-and-play Strategy for Graph-based Recommendation through Decoupled Propagation

Yanping Zheng, Zhewei Wei, Frank de Hoog +4

Graph Neural Networks (GNNs) have demonstrated remarkable effectiveness in recommendation systems. However, conventional graph-based recommenders, such as LightGCN, require maintai…

cs.LG2025

Future Link Prediction Without Memory or Aggregation

Lu Yi, Runlin Lei, Fengran Mo +3

Future link prediction on temporal graphs is a fundamental task with wide applicability in real-world dynamic systems. These scenarios often involve both recurring (seen) and novel…

cs.LG2025★ 1 cited

TGB-Seq Benchmark: Challenging Temporal GNNs with Complex Sequential Dynamics

Lu Yi, Jie Peng, Yanping Zheng +5

Future link prediction is a fundamental challenge in various real-world dynamic systems. To address this, numerous temporal graph neural networks (temporal GNNs) and benchmark data…

cs.LG2025

Rethinking Link Prediction for Directed Graphs

Mingguo He, Yuhe Guo, Yanping Zheng +3

Link prediction for directed graphs is a crucial task with diverse real-world applications. Recent advances in embedding methods and Graph Neural Networks (GNNs) have shown promisi…

cs.LG2024★ 2 cited

A survey of dynamic graph neural networks

Yanping Zheng, Lu Yi, Zhewei Wei

Graph neural networks (GNNs) have emerged as a powerful tool for effectively mining and learning from graph-structured data, with applications spanning numerous domains. However, m…

cs.LG2023★ 1 cited

Decoupled Graph Neural Networks for Large Dynamic Graphs

Yanping Zheng, Zhewei Wei, Jiajun Liu

Real-world graphs, such as social networks, financial transactions, and recommendation systems, often demonstrate dynamic behavior. This phenomenon, known as graph stream, involves…

cs.LG2022★ 1 cited

Instant Graph Neural Networks for Dynamic Graphs

Yanping Zheng, Hanzhi Wang, Zhewei Wei +2

Graph Neural Networks (GNNs) have been widely used for modeling graph-structured data. With the development of numerous GNN variants, recent years have witnessed groundbreaking res…