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 1501–1525 of 1860 papers

Title	Date	Tasks	Status	Hype
A Self-Attention Network based Node Embedding Model	Jun 22, 2020	General ClassificationLink Prediction	CodeCode Available	1
Connecting Graph Convolutional Networks and Graph-Regularized PCA	Jun 22, 2020	Node Classification	—Unverified	0
Graph Neural Networks in TensorFlow and Keras with Spektral	Jun 22, 2020	Deep LearningGeneral Classification	CodeCode Available	2
Graph Backdoor	Jun 21, 2020	Backdoor AttackDescriptive	CodeCode Available	1
Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs	Jun 20, 2020	Graph Neural NetworkNode Classification	CodeCode Available	1
Backdoor Attacks to Graph Neural Networks	Jun 19, 2020	Backdoor AttackGeneral Classification	CodeCode Available	1
Quantifying Challenges in the Application of Graph Representation Learning	Jun 18, 2020	Graph Representation LearningLink Prediction	—Unverified	0
GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training	Jun 17, 2020	Contrastive LearningGeneral Classification	CodeCode Available	1
NodeNet: A Graph Regularised Neural Network for Node Classification	Jun 16, 2020	ClassificationGeneral Classification	—Unverified	0
Fast Graph Attention Networks Using Effective Resistance Based Graph Sparsification	Jun 15, 2020	Graph AttentionNode Classification	—Unverified	0
Adaptive Universal Generalized PageRank Graph Neural Network	Jun 14, 2020	GPRGraph Neural Network	CodeCode Available	1
Implicit Kernel Attention	Jun 11, 2020	Graph AttentionNode Classification	—Unverified	0
Data Augmentation for Graph Neural Networks	Jun 11, 2020	Data AugmentationGeneral Classification	CodeCode Available	1
Locally Private Graph Neural Networks	Jun 9, 2020	Federated LearningNode Classification	CodeCode Available	1
Little Ball of Fur: A Python Library for Graph Sampling	Jun 8, 2020	Graph ClassificationGraph Embedding	—Unverified	0
Eigen-GNN: A Graph Structure Preserving Plug-in for GNNs	Jun 8, 2020	Dimensionality ReductionLink Prediction	—Unverified	0
Graph Representation Learning Network via Adaptive Sampling	Jun 8, 2020	Graph AttentionGraph Representation Learning	CodeCode Available	0
Understanding Graph Neural Networks from Graph Signal Denoising Perspectives	Jun 8, 2020	DenoisingGraph Attention	CodeCode Available	1
Bayesian Graph Neural Networks with Adaptive Connection Sampling	Jun 7, 2020	Node Classification	CodeCode Available	1
Deep Graph Contrastive Representation Learning	Jun 7, 2020	AttributeContrastive Learning	CodeCode Available	1
Network Together: Node Classification via Cross-Network Deep Network Embedding	Jun 4, 2020	Domain AdaptationGeneral Classification	CodeCode Available	1
Shoestring: Graph-Based Semi-Supervised Classification With Severely Limited Labeled Data	Jun 1, 2020	ClassificationClustering	—Unverified	0
Learning Combinatorial Solver for Graph Matching	Jun 1, 2020	Combinatorial OptimizationGraph Matching	—Unverified	0
Non-Local Graph Neural Networks	May 29, 2020	Node ClassificationNode Classification on Non-Homophilic (Heterophilic) Graphs	CodeCode Available	1
A Process for the Evaluation of Node Embedding Methods in the Context of Node Classification	May 29, 2020	BIG-bench Machine LearningFeature Engineering	—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	NodeNet	Accuracy	86.8	—	Unverified
7	Cleora	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	GGCM	Accuracy	74.2	—	Unverified
6	GEM	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