13 citations · 13 across the 4 of their papers we have counts for
4 papers · 1 filter
Enhancing the Cross-Size Generalization for Solving Vehicle Routing Problems via Continual Learning
Jingwen Li, Zhiguang Cao, Yaoxin Wu +1
Exploring machine learning techniques for addressing vehicle routing problems has attracted considerable research attention. To achieve decent and efficient solutions, existing dee…
Implicit vs Unfolded Graph Neural Networks
Yongyi Yang, Tang Liu, Yangkun Wang +2
It has been observed that message-passing graph neural networks (GNN) sometimes struggle to maintain a healthy balance between the efficient/scalable modeling of long-range depende…
Scaling Up Graph Neural Networks Via Graph Coarsening
Zengfeng Huang, Shengzhong Zhang, Chong Xi +2
Scalability of graph neural networks remains one of the major challenges in graph machine learning. Since the representation of a node is computed by recursively aggregating and tr…
Graph Neural Networks Inspired by Classical Iterative Algorithms
Yongyi Yang, Tang Liu, Yangkun Wang +6
Despite the recent success of graph neural networks (GNN), common architectures often exhibit significant limitations, including sensitivity to oversmoothing, long-range dependenci…