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 11511200 of 1860 papers

TitleStatusHype
A Meta-Learning Approach for Training Explainable Graph Neural NetworksCode1
Embedding Node Structural Role Identity Using Stress Majorization0
HeMI: Multi-view Embedding in Heterogeneous GraphsCode0
Is Heterophily A Real Nightmare For Graph Neural Networks To Do Node Classification?0
Ergodic Limits, Relaxations, and Geometric Properties of Random Walk Node Embeddings0
QUINT: Node embedding using network hashing0
HMSG: Heterogeneous Graph Neural Network based on Metapath Subgraph Learning0
Node Feature Kernels Increase Graph Convolutional Network RobustnessCode0
An Empirical Study of Graph Contrastive LearningCode1
Quantized Convolutional Neural Networks Through the Lens of Partial Differential Equations0
Heterogeneous Graph Neural Network with Multi-view Representation Learning0
Towards Self-Explainable Graph Neural NetworkCode1
Tree Decomposed Graph Neural NetworkCode1
Layer-wise Adaptive Graph Convolution Networks Using Generalized Pagerank0
REFINE: Random RangE FInder for Network Embedding0
Jointly Learnable Data Augmentations for Self-Supervised GNNsCode1
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
Label-informed Graph Structure Learning for Node Classification0
Self-supervised Consensus Representation Learning for Attributed GraphCode0
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
Global Self-Attention as a Replacement for Graph ConvolutionCode1
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
Relational Graph Convolutional Networks: A Closer LookCode1
A Survey on Role-Oriented Network EmbeddingCode1
A Graph Data Augmentation Strategy with Entropy Preservation0
Automated Graph Learning via Population Based Self-Tuning GCN0
Asymptotics of Network Embeddings Learned via SubsamplingCode0
DPPIN: A Biological Repository of Dynamic Protein-Protein Interaction Network DataCode1
Privacy-Preserving Representation Learning on Graphs: A Mutual Information Perspective0
On Positional and Structural Node Features for Graph Neural Networks on Non-attributed GraphsCode1
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
You are AllSet: A Multiset Function Framework for Hypergraph Neural NetworksCode1
NodePiece: Compositional and Parameter-Efficient Representations of Large Knowledge GraphsCode1
A Vertical Federated Learning Framework for Graph Convolutional Network0
Customizing Graph Neural Networks using Path ReweightingCode0
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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