Node Classification

Node Classification is a machine learning task in graph-based data analysis, where the goal is to assign labels to nodes in a graph based on the properties of nodes and the relationships between them.

Node Classification models aim to predict non-existing node properties (known as the target property) based on other node properties. Typical models used for node classification consists of a large family of graph neural networks. Model performance can be measured using benchmark datasets like Cora, Citeseer, and Pubmed, among others, typically using Accuracy and F1.

( Image credit: Fast Graph Representation Learning With PyTorch Geometric )

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 1201–1225 of 1860 papers

Title	Date	Tasks	Status
Simple yet Effective Graph Distillation via Clustering	May 27, 2025	ClusteringGraph Representation Learning	—Unverified
Simplification of Graph Convolutional Networks: A Matrix Factorization-based Perspective	Jul 17, 2020	Community DetectionDistributed Computing	—Unverified
Sketch-GNN: Scalable Graph Neural Networks with Sublinear Training Complexity	Jun 21, 2024	Graph LearningNode Classification	—Unverified
GCN-SL: Graph Convolutional Networks with Structure Learning for Graphs under Heterophily	May 28, 2021	ClusteringNode Classification	—Unverified
Slicing Input Features to Accelerate Deep Learning: A Case Study with Graph Neural Networks	Aug 21, 2024	GPUGraph Learning	—Unverified
Space-Invariant Projection in Streaming Network Embedding	Mar 11, 2023	Network EmbeddingNode Classification	—Unverified
Sparse Decomposition of Graph Neural Networks	Oct 25, 2024	Graph Neural NetworkGraph Representation Learning	—Unverified
Sparse Diffusion-Convolutional Neural Networks	Oct 26, 2017	Computational EfficiencyGeneral Classification	—Unverified
Sparse Spectral Training and Inference on Euclidean and Hyperbolic Neural Networks	May 24, 2024	Link PredictionMachine Translation	—Unverified
SpecSphere: Dual-Pass Spectral-Spatial Graph Neural Networks with Certified Robustness	May 13, 2025	Node Classification	—Unverified
Spectral Embedding of Graph Networks	Sep 30, 2020	Graph EmbeddingNode Classification	—Unverified
Spectral Graph Attention Network with Fast Eigen-approximation	Mar 16, 2020	Graph AttentionNode Classification	—Unverified
Spectral Greedy Coresets for Graph Neural Networks	May 27, 2024	Dataset CondensationNode Classification	—Unverified
Spectral Network Embedding: A Fast and Scalable Method via Sparsity	Jun 7, 2018	Link PredictionNetwork Embedding	—Unverified
Spectro-Riemannian Graph Neural Networks	Feb 1, 2025	Graph Representation LearningLink Prediction	—Unverified
SPGP: Structure Prototype Guided Graph Pooling	Sep 16, 2022	Graph ClassificationGraph Learning	—Unverified
SplitGNN: Splitting GNN for Node Classification with Heterogeneous Attention	Jan 27, 2023	ClassificationFederated Learning	—Unverified
Pitfalls in Link Prediction with Graph Neural Networks: Understanding the Impact of Target-link Inclusion & Better Practices	Jun 1, 2023	Link PredictionNode Classification	—Unverified
Stabilized Self-training with Negative Sampling on Few-labeled Graph Data	Sep 29, 2021	BenchmarkingNode Classification	—Unverified
Statistical physics analysis of graph neural networks: Approaching optimality in the contextual stochastic block model	Mar 3, 2025	Node ClassificationStochastic Block Model	—Unverified
Streaming Graph Neural Networks via Continual Learning	Sep 23, 2020	Continual LearningNode Classification	—Unverified
StrokeNet: Stroke Assisted and Hierarchical Graph Reasoning Networks	Nov 23, 2021	Node ClassificationRelational Reasoning	—Unverified
Structural Imbalance Aware Graph Augmentation Learning	Mar 24, 2023	Graph ClassificationLink Prediction	—Unverified
Structure and Features Fusion with Evidential Graph Convolutional Neural Network for Node Classification	Nov 16, 2021	ClassificationGraph Representation Learning	—Unverified
Structure-Aware DropEdge Towards Deep Graph Convolutional Networks	Jun 21, 2023	Node Classification	—Unverified

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All datasets Citeseer Pubmed Cora CiteSeer with Public Split: fixed 20 nodes per class PubMed with Public Split: fixed 20 nodes per class Cora with Public Split: fixed 20 nodes per class PPI Coauthor CS Cora (0.5%)Cora (1%)Cora (3%)PubMed (0.03%)

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	NodeNet	Accuracy	80.09	—	Unverified
2	SplineCNN	Accuracy	79.2	—	Unverified
3	PathNet	Accuracy (%)	77.98	—	Unverified
4	3ference	Accuracy	76.33	—	Unverified
5	MMA	Accuracy	76.3	—	Unverified
6	PPNP	Accuracy	75.83	—	Unverified
7	CoLinkDist	Accuracy	75.79	—	Unverified
8	CoLinkDistMLP	Accuracy	75.77	—	Unverified
9	APPNP	Accuracy	75.73	—	Unverified
10	Cleora	Accuracy	75.7	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	NodeNet	Accuracy	90.21	—	Unverified
2	CoLinkDist	Accuracy	89.58	—	Unverified
3	CoLinkDistMLP	Accuracy	89.53	—	Unverified
4	PathNet	Accuracy (%)	88.92	—	Unverified
5	3ference	Accuracy	88.9	—	Unverified
6	SplineCNN	Accuracy	88.88	—	Unverified
7	LinkDist	Accuracy	88.86	—	Unverified
8	LinkDistMLP	Accuracy	88.79	—	Unverified
9	PairE	F1	88.57	—	Unverified
10	GCN + Mixup	Accuracy	87.9	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	LinkDist	Accuracy	88.24	—	Unverified
2	CoLinkDist	Accuracy	87.89	—	Unverified
3	3ference	Accuracy	87.78	—	Unverified
4	LinkDistMLP	Accuracy	87.58	—	Unverified
5	CoLinkDistMLP	Accuracy	87.54	—	Unverified
6	Cleora	Accuracy	86.8	—	Unverified
7	NodeNet	Accuracy	86.8	—	Unverified
8	MMA	Accuracy	85.8	—	Unverified
9	GResNet(GAT)	Accuracy	85.5	—	Unverified
10	TransGNN	1:1 Accuracy	85.1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	OGC	Accuracy	77.5	—	Unverified
2	LDS-GNN	Accuracy	75	—	Unverified
3	CPF-tra-APPNP	Accuracy	74.6	—	Unverified
4	G3NN	Accuracy	74.5	—	Unverified
5	GEM	Accuracy	74.2	—	Unverified
6	GGCM	Accuracy	74.2	—	Unverified
7	Truncated Krylov	Accuracy	73.86	—	Unverified
8	SSGC	Accuracy	73.6	—	Unverified
9	OKDEEM	Accuracy	73.53	—	Unverified
10	GCNII	Accuracy	73.4	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	OGC	Accuracy	83.4	—	Unverified
2	CPF-tra-GCNII	Accuracy	83.2	—	Unverified
3	DSGCN	Accuracy	81.9	—	Unverified
4	Truncated Krylov	Accuracy	81.7	—	Unverified
5	SuperGAT MX	Accuracy	81.7	—	Unverified
6	G-APPNP	Accuracy	80.95	—	Unverified
7	GGCM	Accuracy	80.8	—	Unverified
8	GCN(predicted-targets)	Accuracy	80.42	—	Unverified
9	SSGC	Accuracy	80.4	—	Unverified
10	GCNII	Accuracy	80.2	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	OGC	Accuracy	86.9	—	Unverified
2	GCN-TV	Accuracy	86.3	—	Unverified
3	GCNII	Accuracy	85.5	—	Unverified
4	CPF-ind-APPNP	Accuracy	85.3	—	Unverified
5	AIR-GCN	Accuracy	84.7	—	Unverified
6	H-GCN	Accuracy	84.5	—	Unverified
7	G-APPNP	Accuracy	84.31	—	Unverified
8	SuperGAT MX	Accuracy	84.3	—	Unverified
9	DSGCN	Accuracy	84.2	—	Unverified
10	LDS-GNN	Accuracy	84.1	—	Unverified