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 1601–1625 of 1860 papers

Title	Date	Tasks	Status
Factorized Graph Representations for Semi-Supervised Learning from Sparse Data	Mar 5, 2020	General ClassificationManagement	CodeCode Available
EPINE: Enhanced Proximity Information Network Embedding	Mar 4, 2020	Link PredictionNetwork Embedding	—Unverified
PushNet: Efficient and Adaptive Neural Message Passing	Mar 4, 2020	Inductive BiasNode Classification	CodeCode Available
Self-Supervised Graph Representation Learning via Global Context Prediction	Mar 3, 2020	ClusteringGraph Representation Learning	—Unverified
Permutohedral-GCN: Graph Convolutional Networks with Global Attention	Mar 2, 2020	Node Classification	—Unverified
Indirect Adversarial Attacks via Poisoning Neighbors for Graph Convolutional Networks	Feb 19, 2020	General ClassificationNode Classification	—Unverified
Self-Enhanced GNN: Improving Graph Neural Networks Using Model Outputs	Feb 18, 2020	General ClassificationNode Classification	CodeCode Available
Investigating Extensions to Random Walk Based Graph Embedding	Feb 17, 2020	Graph EmbeddingLink Prediction	—Unverified
Vertex-reinforced Random Walk for Network Embedding	Feb 11, 2020	Link PredictionNetwork Embedding	CodeCode Available
Line Hypergraph Convolution Network: Applying Graph Convolution for Hypergraphs	Feb 9, 2020	Node ClassificationRepresentation Learning	—Unverified
Fake News Detection on News-Oriented Heterogeneous Information Networks through Hierarchical Graph Attention	Feb 5, 2020	ArticlesFake News Detection	—Unverified
Explain Graph Neural Networks to Understand Weighted Graph Features in Node Classification	Feb 2, 2020	General ClassificationNode Classification	—Unverified
Which way? Direction-Aware Attributed Graph Embedding	Jan 30, 2020	General ClassificationGraph Embedding	CodeCode Available
Get Rid of Suspended Animation Problem: Deep Diffusive Neural Network on Graph Semi-Supervised Classification	Jan 22, 2020	General ClassificationGraph Learning	CodeCode Available
Graph Ordering: Towards the Optimal by Learning	Jan 18, 2020	Combinatorial OptimizationCommunity Detection	—Unverified
Graph Inference Learning for Semi-supervised Classification	Jan 17, 2020	ClassificationGeneral Classification	—Unverified
Node Masking: Making Graph Neural Networks Generalize and Scale Better	Jan 17, 2020	Node ClassificationTransductive Learning	—Unverified
Document Network Projection in Pretrained Word Embedding Space	Jan 16, 2020	ClusteringGeneral Classification	—Unverified
Graph-FCN for image semantic segmentation	Jan 2, 2020	Deep LearningGeneral Classification	—Unverified
Robust Graph Representation Learning via Neural Sparsification	Jan 1, 2020	Fraud DetectionGraph Representation Learning	CodeCode Available
Unifying Graph Convolutional Networks as Matrix Factorization	Jan 1, 2020	Distributed ComputingNode Classification	—Unverified
Multi-Label Graph Convolutional Network Representation Learning	Dec 26, 2019	Multi-Label ClassificationNode Classification	—Unverified
Neural Subgraph Isomorphism Counting	Dec 25, 2019	Domain AdaptationGraph Learning	CodeCode Available
A Non-negative Symmetric Encoder-Decoder Approach for Community Detection	Dec 24, 2019	ClusteringCommunity Detection	—Unverified
An Attention-based Graph Neural Network for Heterogeneous Structural Learning	Dec 19, 2019	Graph EmbeddingGraph Neural Network	CodeCode Available

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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