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 1576–1600 of 1860 papers

Title	Date	Tasks	Status
Implicit Kernel Attention	Jun 11, 2020	Graph AttentionNode Classification	—Unverified
Little Ball of Fur: A Python Library for Graph Sampling	Jun 8, 2020	Graph ClassificationGraph Embedding	—Unverified
Graph Representation Learning Network via Adaptive Sampling	Jun 8, 2020	Graph AttentionGraph Representation Learning	CodeCode Available
Eigen-GNN: A Graph Structure Preserving Plug-in for GNNs	Jun 8, 2020	Dimensionality ReductionLink Prediction	—Unverified
Learning Combinatorial Solver for Graph Matching	Jun 1, 2020	Combinatorial OptimizationGraph Matching	—Unverified
Shoestring: Graph-Based Semi-Supervised Classification With Severely Limited Labeled Data	Jun 1, 2020	ClassificationClustering	—Unverified
A Process for the Evaluation of Node Embedding Methods in the Context of Node Classification	May 29, 2020	BIG-bench Machine LearningFeature Engineering	—Unverified
Vertically Federated Graph Neural Network for Privacy-Preserving Node Classification	May 25, 2020	ClassificationGeneral Classification	—Unverified
Adversarial Attack on Hierarchical Graph Pooling Neural Networks	May 23, 2020	Adversarial AttackClassification	—Unverified
The Effects of Randomness on the Stability of Node Embeddings	May 20, 2020	General ClassificationNode Classification	CodeCode Available
Learning Representations using Spectral-Biased Random Walks on Graphs	May 19, 2020	Graph EmbeddingLink Prediction	CodeCode Available
Foundations and modelling of dynamic networks using Dynamic Graph Neural Networks: A survey	May 13, 2020	Dynamic Link PredictionEpidemiology	—Unverified
AN-GCN: An Anonymous Graph Convolutional Network Defense Against Edge-Perturbing Attack	May 6, 2020	Adversarial AttackClassification	—Unverified
HopGAT: Hop-aware Supervision Graph Attention Networks for Sparsely Labeled Graphs	Apr 9, 2020	General ClassificationGraph Attention	—Unverified
A Graph Convolutional Network Composition Framework for Semi-supervised Classification	Apr 8, 2020	ClassificationGeneral Classification	—Unverified
Attribute2vec: Deep Network Embedding Through Multi-Filtering GCN	Apr 3, 2020	AttributeLink Prediction	—Unverified
A Unified Non-Negative Matrix Factorization Framework for Semi-Supervised Learning on Graphs	Apr 1, 2020	Node Classification	CodeCode Available
Temporal Network Representation Learning via Historical Neighborhoods Aggregation	Mar 30, 2020	Link PredictionNetwork Embedding	CodeCode Available
Revisiting Over-smoothing in Deep GCNs	Mar 30, 2020	Node Classification	—Unverified
Progressive Graph Convolutional Networks for Semi-Supervised Node Classification	Mar 27, 2020	ClassificationGeneral Classification	CodeCode Available
A Collective Learning Framework to Boost GNN Expressiveness	Mar 26, 2020	ClassificationGeneral Classification	—Unverified
End-to-End Entity Classification on Multimodal Knowledge Graphs	Mar 25, 2020	ClassificationGeneral Classification	CodeCode Available
Spectral Graph Attention Network with Fast Eigen-approximation	Mar 16, 2020	Graph AttentionNode Classification	—Unverified
Unsupervised Graph Embedding via Adaptive Graph Learning	Mar 10, 2020	Clusteringgraph construction	—Unverified
Knowledge Graphs and Knowledge Networks: The Story in Brief	Mar 7, 2020	Knowledge GraphsLink Prediction	—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	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	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