Graph Regression On Zinc 100K

MAE

평가 결과

이 벤치마크에서 각 모델의 성능 결과

		Paper Title
GAT	0.463	Graph Attention Networks
MoNet	0.407	Geometric deep learning on graphs and manifolds using mixture model CNNs
GatedGCN	0.363	Benchmarking Graph Neural Networks
MPNN	0.288	Neural Message Passing for Quantum Chemistry
EGT	0.143	Global Self-Attention as a Replacement for Graph Convolution
ARGNP	0.136	Automatic Relation-aware Graph Network Proliferation
GSN	0.115	Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting
CIN-small	0.094	Weisfeiler and Lehman Go Cellular: CW Networks

0 of 8 row(s) selected.