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cs.LG2024
A Scalable and Effective Alternative to Graph Transformers
Kaan Sancak, Zhigang Hua, Jin Fang +5
Graph Neural Networks (GNNs) have shown impressive performance in graph representation learning, but they face challenges in capturing long-range dependencies due to their limited…
cs.LG2023
Cooperative Minibatching in Graph Neural Networks
Muhammed Fatih Balin, Dominique LaSalle, Ümit V. Çatalyürek
Training large scale Graph Neural Networks (GNNs) requires significant computational resources, and the process is highly data-intensive. One of the most effective ways to reduce r…