Node Classification on Cora with Public Split: fixed 20 nodes per class

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Accuracy

Rank	Model	Accuracy	Paper	Code	Year
1	OGC	86.9%	From Cluster Assumption to Graph Convolution: Graph-based Semi-Supervised Learning Revisited	zhengwang100/ogc_ggcm	2023
2	GCN-TV	86.3%	Re-Think and Re-Design Graph Neural Networks in Spaces of Continuous Graph Diffusion Functionals	Dandy5721/GNN-PDE-COV	2023
3	GCNII	85.5%	Simple and Deep Graph Convolutional Networks	chennnM/GCNII · chennnM/GCNII · zhanglab-aim/cancer-net · +1	2020
4	GRAND	85.4 ± 0.4	Graph Random Neural Network for Semi-Supervised Learning on Graphs	dmlc/dgl · Grand20/grand · zjunet/dropmessage · +6	2020
5	CPF-ind-APPNP	85.3%	Extract the Knowledge of Graph Neural Networks and Go Beyond it: An Effective Knowledge Distillation Framework	BUPT-GAMMA/CPF	2021
6	GCN	85.1 ± 0.7	Classic GNNs are Strong Baselines: Reassessing GNNs for Node Classification	LUOyk1999/tunedGNN	2024
7	AIR-GCN	84.7%	GraphAIR: Graph Representation Learning with Neighborhood Aggregation and Interaction	CRIPAC-DIG/GraphAIR	2019
8	H-GCN	84.5%	Hierarchical Graph Convolutional Networks for Semi-supervised Node Classification	CRIPAC-DIG/H-GCN	2019
9	DAGNN (Ours)	84.4 ± 0.5	Towards Deeper Graph Neural Networks	dmlc/dgl · mengliu1998/DeeperGNN · divelab/DeeperGNN	2020
10	G-APPNP	84.31%	Pre-train and Learn: Preserve Global Information for Graph Neural Networks	zhudanhao/g-gnn	2019
11	SuperGAT MX	84.3%	How to Find Your Friendly Neighborhood: Graph Attention Design with Self-Supervision	pyg-team/pytorch_geometric · dongkwan-kim/SuperGAT	2022
12	DSGCN	84.2%	Bridging the Gap Between Spectral and Spatial Domains in Graph Neural Networks	balcilar/Spectral-Designed-Graph-Convolutions · sidneyarcidiacono/UnderstandingGCNs	2020
13	LDS-GNN	84.1%	Learning Discrete Structures for Graph Neural Networks	lucfra/LDS · lucfra/LDS-GNN	2019
14	GraphMix	83.94 ± 0.57	GraphMix: Improved Training of GNNs for Semi-Supervised Learning	vikasverma1077/GraphMix	2019
15	GraphMix (GCN)	83.94 ± 0.57	GraphMix: Improved Training of GNNs for Semi-Supervised Learning	vikasverma1077/GraphMix	2019
16	GCN+GAugO	83.6 ± 0.5%	Data Augmentation for Graph Neural Networks	zhao-tong/GAug · andyjzhao/wsdm23-gsr	2020
17	GGCM	83.6%	From Cluster Assumption to Graph Convolution: Graph-based Semi-Supervised Learning Revisited	zhengwang100/ogc_ggcm	2023
18	Snowball (linear)	83.26%	Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks	PwnerHarry/Stronger_GCN	2019
19	GAT+PGN	83.26 ± 0.69%	The Split Matters: Flat Minima Methods for Improving the Performance of GNNs	foisunt/fmms-in-gnns	2023
20	Snowball (tanh)	83.19%	Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks	PwnerHarry/Stronger_GCN	2019