Graph Classification On Malnet Tiny

Accuracy

评测结果

各个模型在此基准测试上的表现结果

		Paper Title
ESA (Edge set attention, no positional encodings)	94.800±0.424	An end-to-end attention-based approach for learning on graphs
GatedGCN+	94.600±0.570	Can Classic GNNs Be Strong Baselines for Graph-level Tasks? Simple Architectures Meet Excellence
Exphormer	94.02±0.209	Exphormer: Sparse Transformers for Graphs
GPS	93.36 ± 0.6	Recipe for a General, Powerful, Scalable Graph Transformer

0 of 4 row(s) selected.