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 Systematic Evaluation of Node Embedding RobustnessCode0
DiP-GNN: Discriminative Pre-Training of Graph Neural Networks0
Hub-aware Random Walk Graph Embedding Methods for Classification0
Graph Perceiver IO: A General Architecture for Graph Structured DataCode0
Adversarial Inter-Group Link Injection Degrades the Fairness of Graph Neural NetworksCode0
Semantic2Graph: Graph-based Multi-modal Feature Fusion for Action Segmentation in Videos0
Characterizing Graph Datasets for Node Classification: Homophily-Heterophily Dichotomy and Beyond0
Graph Polynomial Convolution Models for Node Classification of Non-Homophilous Graphs0
Towards Sparsification of Graph Neural NetworksCode0
A Complex Network based Graph Embedding Method for Link Prediction0
Self-supervised Learning for Heterogeneous Graph via Structure Information based on Metapath0
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
Robust Node Classification on Graphs: Jointly from Bayesian Label Transition and Topology-based Label PropagationCode0
Signed Graph Neural Networks: A Frequency Perspective0
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
SGAT: Simplicial Graph Attention NetworkCode0
Understanding Non-linearity in Graph Neural Networks from the Bayesian-Inference PerspectiveCode0
Digraphwave: Scalable Extraction of Structural Node Embeddings via Diffusion on Directed Graphs0
Comprehensive Graph Gradual Pruning for Sparse Training in Graph Neural Networks0
Demystifying Graph Convolution with a Simple Concatenation0
Differentially Private Graph Learning via Sensitivity-Bounded Personalized PageRankCode0
Graph CNN for Moving Object Detection in Complex Environments from Unseen Videos0
From Spectral Graph Convolutions to Large Scale Graph Convolutional Networks0
On Graph Neural Network Fairness in the Presence of Heterophilous Neighborhoods0
Generalization Guarantee of Training Graph Convolutional Networks with Graph Topology Sampling0
What Do Graph Convolutional Neural Networks Learn?Code0
Assessing the Effects of Hyperparameters on Knowledge Graph Embedding QualityCode0
RGL: A Simple yet Effective Relation Graph Augmented Prompt-based Tuning Approach for Few-Shot Learning0
Neural Networks in a Product of Hyperbolic Spaces0
Modularity Optimization as a Training Criterion for Graph Neural NetworksCode0
Geometry Contrastive Learning on Heterogeneous GraphsCode0
Similarity-aware Positive Instance Sampling for Graph Contrastive Pre-training0
Descent Steps of a Relation-Aware Energy Produce Heterogeneous Graph Neural NetworksCode0
Propagation with Adaptive Mask then Training for Node Classification on Attributed Networks0
Beyond Real-world Benchmark Datasets: An Empirical Study of Node Classification with GNNsCode0
DFG-NAS: Deep and Flexible Graph Neural Architecture SearchCode0
ResNorm: Tackling Long-tailed Degree Distribution Issue in Graph Neural Networks via Normalization0
GraphFM: Improving Large-Scale GNN Training via Feature Momentum0
Superiority of GNN over NN in generalizing bandlimited functions0
Semi-Supervised Hierarchical Graph Classification0
Synthetic Over-sampling for Imbalanced Node Classification with Graph Neural Networks0
Fundamental Limits in Formal Verification of Message-Passing Neural Networks0
A Unification Framework for Euclidean and Hyperbolic Graph Neural NetworksCode0
Alternately Optimized Graph Neural Networks0
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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
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