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 876900 of 1860 papers

TitleStatusHype
Heterogeneous Graph Tree NetworksCode1
Cadence Detection in Symbolic Classical Music using Graph Neural Networks0
Associative Learning for Network Embedding0
Toward Robust Graph Semi-Supervised Learning against Extreme Data Scarcity0
LTE4G: Long-Tail Experts for Graph Neural NetworksCode1
Robust Node Classification on Graphs: Jointly from Bayesian Label Transition and Topology-based Label PropagationCode0
Scaling Up Dynamic Graph Representation Learning via Spiking Neural NetworksCode1
Signed Graph Neural Networks: A Frequency Perspective0
GPPT: Graph Pre-training and Prompt Tuning to Generalize Graph Neural NetworksCode1
Multiplex Heterogeneous Graph Convolutional NetworkCode1
E2EG: End-to-End Node Classification Using Graph Topology and Text-based Node AttributesCode0
TPM: Transition Probability Matrix -- Graph Structural Feature based Embedding0
Node Copying: A Random Graph Model for Effective Graph Sampling0
Analysis of the Spatio-temporal Dynamics of COVID-19 in Massachusetts via Spectral Graph Wavelet Theory0
Label-Only Membership Inference Attack against Node-Level Graph Neural Networks0
Generative Subgraph Contrast for Self-Supervised Graph Representation LearningCode1
SGAT: Simplicial Graph Attention NetworkCode0
Understanding Non-linearity in Graph Neural Networks from the Bayesian-Inference PerspectiveCode0
Beyond Homophily: Structure-aware Path Aggregation Graph Neural NetworkCode1
Digraphwave: Scalable Extraction of Structural Node Embeddings via Diffusion on Directed Graphs0
Demystifying Graph Convolution with a Simple Concatenation0
Comprehensive Graph Gradual Pruning for Sparse Training in Graph Neural Networks0
Learning Long-Term Spatial-Temporal Graphs for Active Speaker DetectionCode1
Differentially Private Graph Learning via Sensitivity-Bounded Personalized PageRankCode0
Equivariant Hypergraph Diffusion Neural OperatorsCode1
Show:102550
← PrevPage 36 of 75Next →

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
6CleoraAccuracy86.8Unverified
7NodeNetAccuracy86.8Unverified
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