SOTAVerified

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

Showing 13511400 of 1860 papers

TitleStatusHype
Node Feature Kernels Increase Graph Convolutional Network RobustnessCode0
Heterogeneous Graph Neural Network with Multi-view Representation Learning0
Quantized Convolutional Neural Networks Through the Lens of Partial Differential Equations0
Layer-wise Adaptive Graph Convolution Networks Using Generalized Pagerank0
REFINE: Random RangE FInder for Network Embedding0
A Hard Label Black-box Adversarial Attack Against Graph Neural Networks0
Unsupervised Domain-adaptive Hash for Networks0
Semi-supervised Network Embedding with Differentiable Deep Quantisation0
Blockchain Phishing Scam Detection via Multi-channel Graph Classification0
Temporal Graph Network Embedding with Causal Anonymous Walks RepresentationsCode0
Self-supervised Consensus Representation Learning for Attributed GraphCode0
Label-informed Graph Structure Learning for Node Classification0
A Framework for Joint Unsupervised Learning of Cluster-Aware Embedding for Heterogeneous Networks0
Missing Data Estimation in Temporal Multilayer Position-aware Graph Neural Network (TMP-GNN)0
Evaluating Deep Graph Neural NetworksCode0
Explicit Pairwise Factorized Graph Neural Network for Semi-Supervised Node Classification0
Local2Global: Scaling global representation learning on graphs via local trainingCode0
ROD: Reception-aware Online Distillation for Sparse GraphsCode0
GCExplainer: Human-in-the-Loop Concept-based Explanations for Graph Neural Networks0
Ego-GNNs: Exploiting Ego Structures in Graph Neural Networks0
A Graph Data Augmentation Strategy with Entropy Preservation0
Automated Graph Learning via Population Based Self-Tuning GCN0
Asymptotics of Network Embeddings Learned via SubsamplingCode0
Privacy-Preserving Representation Learning on Graphs: A Mutual Information Perspective0
SearchGCN: Powering Embedding Retrieval by Graph Convolution Networks for E-Commerce Search0
Exploiting Spiking Dynamics with Spatial-temporal Feature Normalization in Graph Learning0
Curvature Graph Neural Network0
Dual GNNs: Graph Neural Network Learning with Limited Supervision0
Simple Truncated SVD based Model for Node Classification on Heterophilic Graphs0
Fea2Fea: Exploring Structural Feature Correlations via Graph Neural NetworksCode0
A Vertical Federated Learning Framework for Graph Convolutional Network0
Customizing Graph Neural Networks using Path ReweightingCode0
GraphMixup: Improving Class-Imbalanced Node Classification on Graphs by Self-supervised Context Prediction0
Large-Scale Network Embedding in Apache Spark0
Self-supervised Incremental Deep Graph Learning for Ethereum Phishing Scam Detection0
RLC-GNN: An Improved Deep Architecture for Spatial-Based Graph Neural Network with Application to Fraud Detection0
SEEN: Sharpening Explanations for Graph Neural Networks using Explanations from Neighborhoods0
Data Augmentation for Graph Convolutional Network on Semi-Supervised Classification0
On the approximation capability of GNNs in node classification/regression tasksCode0
Noise-robust Graph Learning by Estimating and Leveraging Pairwise InteractionsCode0
Node Classification Meets Link Prediction on Knowledge Graphs0
Robust Graph Meta-learning for Weakly-supervised Few-shot Node Classification0
Learnable Hypergraph Laplacian for Hypergraph LearningCode0
Is Homophily a Necessity for Graph Neural Networks?0
Learning Based Proximity Matrix Factorization for Node EmbeddingCode0
AKE-GNN: Effective Graph Learning with Adaptive Knowledge Exchange0
Learnable Hypergraph Laplacian for Hypergraph LearningCode0
Multiple Kernel Representation Learning on NetworksCode0
Vertex-Centric Visual Programming for Graph Neural Networks0
Fairness-Aware Node Representation Learning0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1NodeNetAccuracy80.09Unverified
2SplineCNNAccuracy79.2Unverified
3PathNetAccuracy (%)77.98Unverified
43ferenceAccuracy76.33Unverified
5MMAAccuracy76.3Unverified
6PPNPAccuracy75.83Unverified
7CoLinkDistAccuracy75.79Unverified
8CoLinkDistMLPAccuracy75.77Unverified
9APPNPAccuracy75.73Unverified
10CleoraAccuracy75.7Unverified
#ModelMetricClaimedVerifiedStatus
1NodeNetAccuracy90.21Unverified
2CoLinkDistAccuracy89.58Unverified
3CoLinkDistMLPAccuracy89.53Unverified
4PathNetAccuracy (%)88.92Unverified
53ferenceAccuracy88.9Unverified
6SplineCNNAccuracy88.88Unverified
7LinkDistAccuracy88.86Unverified
8LinkDistMLPAccuracy88.79Unverified
9PairEF188.57Unverified
10GCN + MixupAccuracy87.9Unverified
#ModelMetricClaimedVerifiedStatus
1LinkDistAccuracy88.24Unverified
2CoLinkDistAccuracy87.89Unverified
33ferenceAccuracy87.78Unverified
4LinkDistMLPAccuracy87.58Unverified
5CoLinkDistMLPAccuracy87.54Unverified
6NodeNetAccuracy86.8Unverified
7CleoraAccuracy86.8Unverified
8MMAAccuracy85.8Unverified
9GResNet(GAT)Accuracy85.5Unverified
10TransGNN1:1 Accuracy85.1Unverified
#ModelMetricClaimedVerifiedStatus
1OGCAccuracy77.5Unverified
2LDS-GNNAccuracy75Unverified
3CPF-tra-APPNPAccuracy74.6Unverified
4G3NNAccuracy74.5Unverified
5GEMAccuracy74.2Unverified
6GGCMAccuracy74.2Unverified
7Truncated KrylovAccuracy73.86Unverified
8SSGCAccuracy73.6Unverified
9OKDEEMAccuracy73.53Unverified
10GCNIIAccuracy73.4Unverified
#ModelMetricClaimedVerifiedStatus
1OGCAccuracy83.4Unverified
2CPF-tra-GCNIIAccuracy83.2Unverified
3DSGCNAccuracy81.9Unverified
4Truncated KrylovAccuracy81.7Unverified
5SuperGAT MXAccuracy81.7Unverified
6G-APPNPAccuracy80.95Unverified
7GGCMAccuracy80.8Unverified
8GCN(predicted-targets)Accuracy80.42Unverified
9SSGCAccuracy80.4Unverified
10GCNIIAccuracy80.2Unverified
#ModelMetricClaimedVerifiedStatus
1OGCAccuracy86.9Unverified
2GCN-TVAccuracy86.3Unverified
3GCNIIAccuracy85.5Unverified
4CPF-ind-APPNPAccuracy85.3Unverified
5AIR-GCNAccuracy84.7Unverified
6H-GCNAccuracy84.5Unverified
7G-APPNPAccuracy84.31Unverified
8SuperGAT MXAccuracy84.3Unverified
9DSGCNAccuracy84.2Unverified
10LDS-GNNAccuracy84.1Unverified