Graph Classification on IMDb-M

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Accuracy

Rank	Model	Accuracy	Accuracy (10-fold)	Extra Training Data	Paper	Code	Year
1	U2GNN (Unsupervised)	89.2%	–		Universal Graph Transformer Self-Attention Networks	daiquocnguyen/Graph-Transformer	2019
2	TFGW ADJ (L=2)	56.8%	–		Template based Graph Neural Network with Optimal Transport Distances	cedricvincentcuaz/TFGW	2022
3	TREE-G	56.4%	–		TREE-G: Decision Trees Contesting Graph Neural Networks	mayabechlerspeicher/tree-g	2022
4	MEWISPool	56.23%	–		Maximum Entropy Weighted Independent Set Pooling for Graph Neural Networks	mewispool/mewispool	2021
5	DUGNN	56.10%	–	✓	Learning Universal Graph Neural Network Embeddings With Aid Of Transfer Learning	vermaMachineLearning/Universal-Graph-Embedding-Neural-Network	2019
6	G_ResNet	54.53%	–		When Work Matters: Transforming Classical Network Structures to Graph CNN		2018
7	sGIN	54.52%	–		Mutual Information Maximization in Graph Neural Networks	CODE-SUBMIT/Graph_Neighborhood_1 · CODE-SUBMIT/Neighborhood-Enlargement-in-Graph-Network	2019
8	GIUNet	54%	–		Graph isomorphism UNet	aramiracle/GIUNet	2023
9	U2GNN	53.60%	–		Universal Graph Transformer Self-Attention Networks	daiquocnguyen/Graph-Transformer	2019
10	SEG-BERT	53.4%	–		Segmented Graph-Bert for Graph Instance Modeling	jwzhanggy/SEG-BERT	2020
11	GIN-0	52.3%	–		How Powerful are Graph Neural Networks?	dmlc/dgl · dmlc/dgl · weihua916/powerful-gnns · +16	2018
12	WEGL	52%	–		Wasserstein Embedding for Graph Learning	navid-naderi/WEGL	2020
13	GFN	51.80%	–		Are Powerful Graph Neural Nets Necessary? A Dissection on Graph Classification	chentingpc/gfn	2019
14	1-WL Kernel	51.5%	–		Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks	chrsmrrs/k-gnn	2018
15	DropGIN	51.4%	–		DropGNN: Random Dropouts Increase the Expressiveness of Graph Neural Networks	karolismart/dropgnn	2021
16	GFN-light	51.20%	–		Are Powerful Graph Neural Nets Necessary? A Dissection on Graph Classification	chentingpc/gfn	2019
17	UGraphEmb-F	50.97%	–		Unsupervised Inductive Graph-Level Representation Learning via Graph-Graph Proximity	yunshengb/UGraphEmb	2019
18	Graph-JEPA	50.69%	–		Graph-level Representation Learning with Joint-Embedding Predictive Architectures	geriskenderi/graph-jepa	2023
19	GMT	50.66%	–		Accurate Learning of Graph Representations with Graph Multiset Pooling	JinheonBaek/GMT	2021
20	GDL	50.64%	–		Online Graph Dictionary Learning	cedricvincentcuaz/GDL	2021