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

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Showing 601–625 of 1860 papers

Title	Date	Tasks	Status
Graph Joint Attention Networks	Sep 28, 2020	BenchmarkingGraph Attention	—Unverified
Bayesian Graph Neural Network for Fast identification of critical nodes in Uncertain Complex Networks	Dec 26, 2020	Graph Neural NetworkNode Classification	—Unverified
Graph Convolutional Network For Semi-supervised Node Classification With Subgraph Sketching	Apr 19, 2024	ClassificationClustering	—Unverified
Density-Aware Hyper-Graph Neural Networks for Graph-based Semi-supervised Node Classification	Jan 27, 2022	ClassificationGraph Attention	—Unverified
AmGCL: Feature Imputation of Attribute Missing Graph via Self-supervised Contrastive Learning	May 5, 2023	AttributeContrastive Learning	—Unverified
Graph Learning for Anomaly Analytics: Algorithms, Applications, and Challenges	Dec 11, 2022	Graph AttentionGraph Classification	—Unverified
Demystifying Graph Convolution with a Simple Concatenation	Jul 18, 2022	Graph LearningNode Classification	—Unverified
Bayesian Graph Convolutional Neural Networks using Node Copying	Nov 8, 2019	Node Classification	—Unverified
Graph Information Matters: Understanding Graph Filters from Interaction Probability	Sep 29, 2021	Graph LearningNode Classification	—Unverified
Bayesian Graph Convolutional Neural Networks Using Non-Parametric Graph Learning	Oct 26, 2019	Bayesian InferenceGeneral Classification	—Unverified
A Deep Graph Neural Networks Architecture Design: From Global Pyramid-like Shrinkage Skeleton to Local Topology Link Rewiring	Dec 16, 2020	ClusteringNode Classification	—Unverified
GraphiT: Efficient Node Classification on Text-Attributed Graphs with Prompt Optimized LLMs	Feb 14, 2025	Node Classification	—Unverified
DELATOR: Money Laundering Detection via Multi-Task Learning on Large Transaction Graphs	May 20, 2022	Financial AnalysisMulti-Task Learning	—Unverified
Alternately Optimized Graph Neural Networks	Jun 8, 2022	MULTI-VIEW LEARNINGNode Classification	—Unverified
DeHIN: A Decentralized Framework for Embedding Large-scale Heterogeneous Information Networks	Jan 8, 2022	Link PredictionNetwork Embedding	—Unverified
Degree-Quant: Quantization-Aware Training for Graph Neural Networks	Aug 11, 2020	CPUGraph Classification	—Unverified
A Magnetic Framelet-Based Convolutional Neural Network for Directed Graphs	Oct 20, 2022	DenoisingLink Prediction	—Unverified
Batch Virtual Adversarial Training for Graph Convolutional Networks	Feb 25, 2019	General ClassificationNode Classification	—Unverified
Degree-Based Random Walk Approach for Graph Embedding	Oct 21, 2021	Graph EmbeddingLink Prediction	—Unverified
Barlow Graph Auto-Encoder for Unsupervised Network Embedding	Oct 29, 2021	Inductive Link PredictionLink Prediction	—Unverified
DeGLIF for Label Noise Robust Node Classification using GNNs	May 30, 2025	DenoisingNode Classification	—Unverified
10,000+ Times Accelerated Robust Subset Selection (ARSS)	Sep 12, 2014	10-shot image generationAction Recognition	—Unverified
Graph Infomax Adversarial Learning for Treatment Effect Estimation with Networked Observational Data	Jun 5, 2021	Causal InferenceGraph Learning	—Unverified
Heterophilic Graph Neural Networks Optimization with Causal Message-passing	Nov 21, 2024	Causal InferenceGraph Learning	—Unverified
A Local Graph Limits Perspective on Sampling-Based GNNs	Oct 17, 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	DifNet	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