Graph Classification on REDDIT-B

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Accuracy

Rank	Model	Accuracy	Accuracy (10-fold)	Paper	Code	Year
1	CRaWl	93.15	–	Walking Out of the Weisfeiler Leman Hierarchy: Graph Learning Beyond Message Passing	toenshoff/CRaWl	2021
2	GAT-GC (f-Scaled)	92.57	–	Improving Attention Mechanism in Graph Neural Networks via Cardinality Preservation	zetayue/CPA	2019
3	GIN-0	92.4	–	How Powerful are Graph Neural Networks?	dmlc/dgl · dmlc/dgl · weihua916/powerful-gnns · +16	2018
4	DiffPool	92.1	–	Fast Graph Representation Learning with PyTorch Geometric	rusty1s/pytorch_geometric · leojklarner/gauche · ncfrey/litmatter · +3	2019
5	WEGL	92	–	Wasserstein Embedding for Graph Learning	navid-naderi/WEGL	2020
6	Local Topological Profile (LTP)	91.1 ± 1.0	91.1 ± 1.0	Strengthening structural baselines for graph classification using Local Topological Profile	j-adamczyk/ltp	2023
7	2-WL-GNN	89.4	–	A Novel Higher-order Weisfeiler-Lehman Graph Convolution	Cortys/master-thesis	2020
8	δ-2-LWL	89.0	–	Weisfeiler and Leman go sparse: Towards scalable higher-order graph embeddings	chrsmrrs/sparsewl	2019
9	NDP	84.3	–	Hierarchical Representation Learning in Graph Neural Networks with Node Decimation Pooling	danielegrattarola/decimation-pooling	2019
9	GraphSAGE	84.3	–	A Fair Comparison of Graph Neural Networks for Graph Classification	diningphil/gnn-comparison · diningphil/CGMM · FilippoMB/Pyramidal-Reservoir-Graph-Nerual-Networks · +2	2019
11	ApproxRepSet	80.3	–	Rep the Set: Neural Networks for Learning Set Representations	giannisnik/repset	2019
12	Graph-JEPA	56.73	–	Graph-level Representation Learning with Joint-Embedding Predictive Architectures	geriskenderi/graph-jepa	2023
13	CRaWl	93.15	–	Walking Out of the Weisfeiler Leman Hierarchy: Graph Learning Beyond Message Passing	toenshoff/CRaWl	2021
14	GAT-GC (f-Scaled)	92.57	–	Improving Attention Mechanism in Graph Neural Networks via Cardinality Preservation	zetayue/CPA	2019
15	GIN-0	92.4	–	How Powerful are Graph Neural Networks?	dmlc/dgl · dmlc/dgl · weihua916/powerful-gnns · +16	2018
16	DiffPool	92.1	–	Fast Graph Representation Learning with PyTorch Geometric	rusty1s/pytorch_geometric · leojklarner/gauche · ncfrey/litmatter · +3	2019
17	WEGL	92	–	Wasserstein Embedding for Graph Learning	navid-naderi/WEGL	2020
18	Local Topological Profile (LTP)	91.1 ± 1.0	91.1 ± 1.0	Strengthening structural baselines for graph classification using Local Topological Profile	j-adamczyk/ltp	2023
19	2-WL-GNN	89.4	–	A Novel Higher-order Weisfeiler-Lehman Graph Convolution	Cortys/master-thesis	2020
20	δ-2-LWL	89.0	–	Weisfeiler and Leman go sparse: Towards scalable higher-order graph embeddings	chrsmrrs/sparsewl	2019