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 1001–1025 of 1860 papers

Title	Date	Tasks	Status	Hype
View-Consistent Heterogeneous Network on Graphs With Few Labeled Nodes	Mar 17, 2022	Node ClassificationSelf-Supervised Learning	CodeCode Available	1
Supervised Contrastive Learning with Structure Inference for Graph Classification	Mar 15, 2022	ClassificationContrastive Learning	—Unverified	0
GRAND+: Scalable Graph Random Neural Networks	Mar 12, 2022	Data AugmentationGraph Learning	CodeCode Available	1
Shift-Robust Node Classification via Graph Adversarial Clustering	Mar 7, 2022	ClassificationClustering	—Unverified	0
Defending Graph Convolutional Networks against Dynamic Graph Perturbations via Bayesian Self-supervision	Mar 7, 2022	Node ClassificationSelf-Supervised Learning	CodeCode Available	0
Deep Partial Multiplex Network Embedding	Mar 5, 2022	Link PredictionNetwork Embedding	—Unverified	0
R-GCN: The R Could Stand for Random	Mar 4, 2022	Knowledge GraphsLink Prediction	CodeCode Available	1
Graph Representation Learning Beyond Node and Homophily	Mar 3, 2022	Edge ClassificationGraph Embedding	CodeCode Available	0
Pay Attention to Relations: Multi-embeddings for Attributed Multiplex Networks	Mar 3, 2022	Community DetectionLink Prediction	—Unverified	0
GAP: Differentially Private Graph Neural Networks with Aggregation Perturbation	Mar 2, 2022	Node Classification	CodeCode Available	1
Graph Attention Retrospective	Feb 26, 2022	Graph AttentionNode Classification	CodeCode Available	1
MuMiN: A Large-Scale Multilingual Multimodal Fact-Checked Misinformation Social Network Dataset	Feb 23, 2022	ArticlesMisinformation	CodeCode Available	1
Exploring Edge Disentanglement for Node Classification	Feb 23, 2022	ClassificationDisentanglement	—Unverified	0
Graph Masked Autoencoders with Transformers	Feb 17, 2022	DecoderGraph Classification	CodeCode Available	1
When Does A Spectral Graph Neural Network Fail in Node Classification?	Feb 16, 2022	Graph LearningGraph Neural Network	—Unverified	0
Random Laplacian Features for Learning with Hyperbolic Space	Feb 14, 2022	Graph LearningNode Classification	CodeCode Available	1
Adversarial Graph Contrastive Learning with Information Regularization	Feb 14, 2022	Contrastive LearningData Augmentation	CodeCode Available	0
Learning Asymmetric Embedding for Attributed Networks via Convolutional Neural Network	Feb 13, 2022	Graph Neural NetworkLink Prediction	—Unverified	0
Geometric Graph Representation Learning via Maximizing Rate Reduction	Feb 13, 2022	Community DetectionContrastive Learning	—Unverified	0
Neural Sheaf Diffusion: A Topological Perspective on Heterophily and Oversmoothing in GNNs	Feb 9, 2022	Node ClassificationNode Classification on Non-Homophilic (Heterophilic) Graphs	CodeCode Available	1
Simplified Graph Convolution with Heterophily	Feb 8, 2022	Node Classification	CodeCode Available	0
FMP: Toward Fair Graph Message Passing against Topology Bias	Feb 8, 2022	Contrastive LearningFairness	—Unverified	0
Bandit Sampling for Multiplex Networks	Feb 8, 2022	Link PredictionNode Classification	—Unverified	0
Neural Models for Output-Space Invariance in Combinatorial Problems	Feb 7, 2022	Node Classification	—Unverified	0
Graph Neural Network with Curriculum Learning for Imbalanced Node Classification	Feb 5, 2022	ClassificationGraph Classification	—Unverified	0

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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	SuperGAT MX	Accuracy	81.7	—	Unverified
5	Truncated Krylov	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