AI RESEARCH
A Comprehensive Graph Pooling Benchmark: Effectiveness, Robustness and Generalizability
arXiv CS.LG
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ArXi:2406.09031v5 Announce Type: replace Graph pooling has gained attention for its ability to obtain effective node and graph representations for various downstream tasks. Despite the recent surge in graph pooling approaches, there is a lack of standardized experimental settings and fair benchmarks to evaluate their performance. To address this issue, we have constructed a comprehensive benchmark that includes 17 graph pooling methods and 28 different graph datasets.