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 16511700 of 1860 papers

TitleStatusHype
Ordinary differential equations on graph networks0
PINE: Universal Deep Embedding for Graph Nodes via Partial Permutation Invariant Set Functions0
GraphMix: Improved Training of GNNs for Semi-Supervised LearningCode0
Node Injection Attacks on Graphs via Reinforcement Learning0
GResNet: Graph Residual Network for Reviving Deep GNNs from Suspended AnimationCode0
Kernel Node EmbeddingsCode0
Measuring and Relieving the Over-smoothing Problem for Graph Neural Networks from the Topological View0
Auto-GNN: Neural Architecture Search of Graph Neural Networks0
Graph Representation Ensemble LearningCode0
Graph Transfer Learning via Adversarial Domain Adaptation with Graph ConvolutionCode0
Deep Graph Library: A Graph-Centric, Highly-Performant Package for Graph Neural NetworksCode0
Graph Convolutional Networks for Road NetworksCode1
Adversarial Training Methods for Network EmbeddingCode1
hpGAT: High-order Proximity Informed Graph Attention Network0
Bayes EMbedding (BEM): Refining Representation by Integrating Knowledge Graphs and Behavior-specific NetworksCode0
Initialization for Network Embedding: A Graph Partition Approach0
Inducing a Decision Tree with Discriminative Paths to Classify Entities in a Knowledge GraphCode0
motif2vec: Motif Aware Node Representation Learning for Heterogeneous Networks0
MEGAN: A Generative Adversarial Network for Multi-View Network Embedding0
AHINE: Adaptive Heterogeneous Information Network Embedding0
Transferring Robustness for Graph Neural Network Against Poisoning AttacksCode0
HONEM: Learning Embedding for Higher Order Networks0
End-to-End Learning from Complex Multigraphs with Latent-Graph Convolutional NetworksCode0
AdaGCN: Adaboosting Graph Convolutional Networks into Deep ModelsCode0
Deep Hashing for Signed Social Network Embedding0
CensNet: Convolution with Edge-Node Switching in Graph Neural Networks0
HATS: A Hierarchical Graph Attention Network for Stock Movement PredictionCode0
Multi-Relational Classification via Bayesian Ranked Non-Linear Embeddings0
DropEdge: Towards Deep Graph Convolutional Networks on Node ClassificationCode1
Semi-Supervised Tensor Factorization for Node Classification in Complex Social Networks0
Node Attribute Generation on GraphsCode1
Improving Skip-Gram based Graph Embeddings via Centrality-Weighted Sampling0
Snomed2Vec: Random Walk and Poincaré Embeddings of a Clinical Knowledge Base for Healthcare AnalyticsCode0
k-hop Graph Neural NetworksCode0
Semi-Supervised Graph Embedding for Multi-Label Graph Node Classification0
GraphSAINT: Graph Sampling Based Inductive Learning MethodCode1
Label-Aware Graph Convolutional Networks0
Fast Haar Transforms for Graph Neural Networks0
Improving Attention Mechanism in Graph Neural Networks via Cardinality PreservationCode0
Dimensional Reweighting Graph Convolutional NetworksCode0
Structure fusion based on graph convolutional networks for semi-supervised classification0
Certifiable Robustness and Robust Training for Graph Convolutional NetworksCode0
Signed Graph Attention NetworksCode1
Graph Star Net for Generalized Multi-Task LearningCode0
Regional based query in graph active learningCode0
ANAE: Learning Node Context Representation for Attributed Network Embedding0
Homogeneous Network Embedding for Massive Graphs via Reweighted Personalized PageRank0
Identifying Illicit Accounts in Large Scale E-payment Networks -- A Graph Representation Learning Approach0
Graph Embedding on Biomedical Networks: Methods, Applications, and EvaluationsCode0
Heterogeneous network approach to predict individuals' mental health0
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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