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 701750 of 1860 papers

TitleStatusHype
Hard Masking for Explaining Graph Neural Networks0
Curvature Graph Neural Network0
Haar Wavelet Feature Compression for Quantized Graph Convolutional Networks0
GPatcher: A Simple and Adaptive MLP Model for Alleviating Graph Heterophily0
Curriculum Learning for Graph Neural Networks: A Multiview Competence-based Approach0
Graph Agent Network: Empowering Nodes with Inference Capabilities for Adversarial Resilience0
HAGNN: Hybrid Aggregation for Heterogeneous Graph Neural Networks0
Gophormer: Ego-Graph Transformer for Node Classification0
Graph Anomaly Detection with Graph Neural Networks: Current Status and Challenges0
GNNLens: A Visual Analytics Approach for Prediction Error Diagnosis of Graph Neural Networks0
De Bruijn goes Neural: Causality-Aware Graph Neural Networks for Time Series Data on Dynamic Graphs0
Automated Graph Learning via Population Based Self-Tuning GCN0
GUAP: Graph Universal Attack Through Adversarial Patching0
G-SPARC: SPectral ARchitectures tackling the Cold-start problem in Graph learning0
Fast Haar Transforms for Graph Neural Networks0
Automated Knowledge Modeling for Cancer Clinical Practice Guidelines0
Graph Attention Networks with Positional Embeddings0
HC-GAE: The Hierarchical Cluster-based Graph Auto-Encoder for Graph Representation Learning0
GNN-MultiFix: Addressing the pitfalls for GNNs for multi-label node classification0
A Unified Framework of Graph Information Bottleneck for Robustness and Membership Privacy0
GNNEvaluator: Evaluating GNN Performance On Unseen Graphs Without Labels0
GNNDLD: Graph Neural Network with Directional Label Distribution0
Crypto'Graph: Leveraging Privacy-Preserving Distributed Link Prediction for Robust Graph Learning0
GraphSOS: Graph Sampling and Order Selection to Help LLMs Understand Graphs Better0
GNNAnatomy: Rethinking Model-Level Explanations for Graph Neural Networks0
Class-Balanced and Reinforced Active Learning on Graphs0
Global Node Attentions via Adaptive Spectral Filters0
Global-Local Graph Neural Networks for Node-Classification0
Graph CNN for Moving Object Detection in Complex Environments from Unseen Videos0
Deep Feature Learning of Multi-Network Topology for Node Classification0
A graph similarity for deep learning0
GRE^2-MDCL: Graph Representation Embedding Enhanced via Multidimensional Contrastive Learning0
Grimm: A Plug-and-Play Perturbation Rectifier for Graph Neural Networks Defending against Poisoning Attacks0
Crossformer: Transformer with Alternated Cross-Layer Guidance0
CPT: Competence-progressive Training Strategy for Few-shot Node Classification0
Graph U-Net0
Graph View-Consistent Learning Network0
Graph Convolution: A High-Order and Adaptive Approach0
Coupled Hierarchical Structure Learning using Tree-Wasserstein Distance0
Effective backdoor attack on graph neural networks in link prediction tasks0
Geometric Pooling: maintaining more useful information0
A Vertical Federated Learning Framework for Graph Convolutional Network0
A Tutorial on Online Supervised Learning with Applications to Node Classification in Social Networks0
GraphViz2Vec: A Structure-aware Feature Generation Model to Improve Classification in GNNs0
HCL: Improving Graph Representation with Hierarchical Contrastive Learning0
Hierarchical Randomized Smoothing0
Geometric Multimodal Deep Learning with Multi-Scaled Graph Wavelet Convolutional Network0
Geometric Graph Representation Learning via Maximizing Rate Reduction0
Each Graph is a New Language: Graph Learning with LLMs0
Co-Representation Neural Hypergraph Diffusion for Edge-Dependent Node Classification0
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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
4SuperGAT MXAccuracy81.7Unverified
5Truncated KrylovAccuracy81.7Unverified
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