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 1151–1175 of 1860 papers

Title	Date	Tasks	Status
A Systematic Evaluation of Node Embedding Robustness	Sep 16, 2022	ClassificationNode Classification	CodeCode Available
DiP-GNN: Discriminative Pre-Training of Graph Neural Networks	Sep 15, 2022	Graph Neural NetworkNode Classification	—Unverified
Hub-aware Random Walk Graph Embedding Methods for Classification	Sep 15, 2022	ClassificationGraph Embedding	—Unverified
Graph Perceiver IO: A General Architecture for Graph Structured Data	Sep 14, 2022	Graph ClassificationLink Prediction	CodeCode Available
Adversarial Inter-Group Link Injection Degrades the Fairness of Graph Neural Networks	Sep 13, 2022	FairnessNode Classification	CodeCode Available
Semantic2Graph: Graph-based Multi-modal Feature Fusion for Action Segmentation in Videos	Sep 13, 2022	Action SegmentationGraph Neural Network	—Unverified
Characterizing Graph Datasets for Node Classification: Homophily-Heterophily Dichotomy and Beyond	Sep 13, 2022	InformativenessNode Classification	—Unverified
Graph Polynomial Convolution Models for Node Classification of Non-Homophilous Graphs	Sep 12, 2022	Generalization BoundsNode Classification	—Unverified
Towards Sparsification of Graph Neural Networks	Sep 11, 2022	image-classificationImage Classification	CodeCode Available
A Complex Network based Graph Embedding Method for Link Prediction	Sep 11, 2022	Data VisualizationGraph Embedding	—Unverified
Self-supervised Learning for Heterogeneous Graph via Structure Information based on Metapath	Sep 9, 2022	Link PredictionMeta-Learning	—Unverified
Cadence Detection in Symbolic Classical Music using Graph Neural Networks	Aug 31, 2022	Key DetectionNode Classification	—Unverified
Associative Learning for Network Embedding	Aug 30, 2022	Network EmbeddingNode Classification	—Unverified
Toward Robust Graph Semi-Supervised Learning against Extreme Data Scarcity	Aug 26, 2022	Data AugmentationNode Classification	—Unverified
Robust Node Classification on Graphs: Jointly from Bayesian Label Transition and Topology-based Label Propagation	Aug 21, 2022	Adversarial DefenseDenoising	CodeCode Available
Signed Graph Neural Networks: A Frequency Perspective	Aug 15, 2022	Link Sign PredictionNode Classification	—Unverified
E2EG: End-to-End Node Classification Using Graph Topology and Text-based Node Attributes	Aug 9, 2022	ClassificationNode Classification	CodeCode Available
TPM: Transition Probability Matrix -- Graph Structural Feature based Embedding	Aug 7, 2022	Link PredictionNode Classification	—Unverified
Node Copying: A Random Graph Model for Effective Graph Sampling	Aug 4, 2022	Graph SamplingNode Classification	—Unverified
Analysis of the Spatio-temporal Dynamics of COVID-19 in Massachusetts via Spectral Graph Wavelet Theory	Jul 28, 2022	Graph AttentionNode Classification	—Unverified
Label-Only Membership Inference Attack against Node-Level Graph Neural Networks	Jul 27, 2022	Graph ClassificationInference Attack	—Unverified
SGAT: Simplicial Graph Attention Network	Jul 24, 2022	Graph AttentionGraph Learning	CodeCode Available
Understanding Non-linearity in Graph Neural Networks from the Bayesian-Inference Perspective	Jul 22, 2022	Bayesian InferenceNode Classification	CodeCode Available
Digraphwave: Scalable Extraction of Structural Node Embeddings via Diffusion on Directed Graphs	Jul 20, 2022	Anomaly DetectionNode Classification	—Unverified
Comprehensive Graph Gradual Pruning for Sparse Training in Graph Neural Networks	Jul 18, 2022	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