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 901950 of 1860 papers

TitleStatusHype
Deceptive Fairness Attacks on Graphs via Meta LearningCode0
Generative and Contrastive Paradigms Are Complementary for Graph Self-Supervised Learning0
GNNEvaluator: Evaluating GNN Performance On Unseen Graphs Without Labels0
A Study on Knowledge Graph Embeddings and Graph Neural Networks for Web Of ThingsCode0
HetGPT: Harnessing the Power of Prompt Tuning in Pre-Trained Heterogeneous Graph Neural Networks0
Fairness-aware Optimal Graph Filter Design0
Neighborhood Homophily-Guided Graph Convolutional NetworkCode0
Positive-Unlabeled Node Classification with Structure-aware Graph Learning0
Exploring Graph Neural Networks for Indian Legal Judgment Prediction0
MuseGNN: Interpretable and Convergent Graph Neural Network Layers at Scale0
Hetero^2Net: Heterophily-aware Representation Learning on Heterogenerous Graphs0
Privacy-Preserving Graph Embedding based on Local Differential PrivacyCode0
A Local Graph Limits Perspective on Sampling-Based GNNs0
SignGT: Signed Attention-based Graph Transformer for Graph Representation Learning0
Topology-guided Hypergraph Transformer Network: Unveiling Structural Insights for Improved Representation0
Causality and Independence Enhancement for Biased Node ClassificationCode0
Heterophily-Based Graph Neural Network for Imbalanced Classification0
Non-backtracking Graph Neural NetworksCode0
Enhanced Graph Neural Networks with Ego-Centric Spectral Subgraph Embeddings AugmentationCode0
Simple GNNs with Low Rank Non-parametric AggregatorsCode0
DeepHGCN: Toward Deeper Hyperbolic Graph Convolutional NetworksCode0
HoloNets: Spectral Convolutions do extend to Directed GraphsCode0
Distilling Influences to Mitigate Prediction Churn in Graph Neural NetworksCode0
The Map Equation Goes Neural: Mapping Network Flows with Graph Neural NetworksCode0
Deep Insights into Noisy Pseudo Labeling on Graph DataCode0
NP^2L: Negative Pseudo Partial Labels Extraction for Graph Neural Networks0
Sheaf Hypergraph Networks0
Prototype-Enhanced Hypergraph Learning for Heterogeneous Information Networks0
Article Classification with Graph Neural Networks and MultigraphsCode0
Crypto'Graph: Leveraging Privacy-Preserving Distributed Link Prediction for Robust Graph Learning0
Semi-supervised Domain Adaptation on Graphs with Contrastive Learning and Minimax EntropyCode0
Bregman Graph Neural NetworkCode0
UniKG: A Benchmark and Universal Embedding for Large-Scale Knowledge GraphsCode0
Force-directed graph embedding with hops distanceCode0
Symplectic Structure-Aware Hamiltonian (Graph) Embeddings0
Curve Your Attention: Mixed-Curvature Transformers for Graph Representation Learning0
Towards Unsupervised Graph Completion Learning on Graphs with Features and Structure Missing0
End-to-End Learning on Multimodal Knowledge GraphsCode0
ConCur: Self-supervised graph representation based on contrastive learning with curriculum negative samplingCode0
Rank Collapse Causes Over-Smoothing and Over-Correlation in Graph Neural NetworksCode0
Domain-adaptive Message Passing Graph Neural NetworkCode0
Low-bit Quantization for Deep Graph Neural Networks with Smoothness-aware Message PropagationCode0
Over-Squashing in Graph Neural Networks: A Comprehensive survey0
A Hybrid Membership Latent Distance Model for Unsigned and Signed Integer Weighted NetworksCode0
Universal Graph Continual Learning0
Unveiling the Role of Message Passing in Dual-Privacy Preservation on GNNs0
Cached Operator Reordering: A Unified View for Fast GNN Training0
Geometric instability of graph neural networks on large graphsCode0
Investigating the Interplay between Features and Structures in Graph LearningCode0
Disparity, Inequality, and Accuracy Tradeoffs in Graph Neural Networks for Node ClassificationCode0
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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