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 12511300 of 1860 papers

TitleStatusHype
Simplified Graph Convolution with HeterophilyCode0
Bandit Sampling for Multiplex Networks0
FMP: Toward Fair Graph Message Passing against Topology Bias0
Neural Models for Output-Space Invariance in Combinatorial Problems0
Graph Neural Network with Curriculum Learning for Imbalanced Node Classification0
Dimensionality Reduction Meets Message Passing for Graph Node EmbeddingsCode0
Investigating Transfer Learning in Graph Neural Networks0
Learning Robust Representation through Graph Adversarial Contrastive Learning0
SMGRL: Scalable Multi-resolution Graph Representation LearningCode0
Density-Aware Hyper-Graph Neural Networks for Graph-based Semi-supervised Node Classification0
Partition-Based Active Learning for Graph Neural NetworksCode0
Joint Learning of Hierarchical Community Structure and Node Representations: An Unsupervised Approach0
Fair Node Representation Learning via Adaptive Data Augmentation0
Enhancing Hyperbolic Graph Embeddings via Contrastive Learning0
Informative Pseudo-Labeling for Graph Neural Networks with Few Labels0
RGL: A Simple yet Effective Relation Graph Augmented Prompt-based Tuning Approach for Few-Shot LearningCode0
Quasi-Framelets: Robust Graph Neural Networks via Adaptive Framelet ConvolutionCode0
DeHIN: A Decentralized Framework for Embedding Large-scale Heterogeneous Information Networks0
Neighbor2vec: an efficient and effective method for Graph Embedding0
Asymptotics of _2 Regularized Network EmbeddingsCode0
Graph Decipher: A transparent dual-attention graph neural network to understand the message-passing mechanism for the node classification0
Toward the Analysis of Graph Neural Networks0
D-HYPR: Harnessing Neighborhood Modeling and Asymmetry Preservation for Digraph Representation LearningCode0
SkipNode: On Alleviating Performance Degradation for Deep Graph Convolutional NetworksCode0
A Comprehensive Analytical Survey on Unsupervised and Semi-Supervised Graph Representation Learning Methods0
Time-Aware Neighbor Sampling for Temporal Graph Networks0
BGL: GPU-Efficient GNN Training by Optimizing Graph Data I/O and Preprocessing0
Neighborhood Random Walk Graph Sampling for Regularized Bayesian Graph Convolutional Neural Networks0
On the Use of Unrealistic Predictions in Hundreds of Papers Evaluating Graph Representations0
A Piece-wise Polynomial Filtering Approach for Graph Neural NetworksCode0
Learning Theory Can (Sometimes) Explain Generalisation in Graph Neural Networks0
Trivial bundle embeddings for learning graph representations0
Multi-scale Graph Convolutional Networks with Self-Attention0
Learning Spatial-Temporal Graphs for Active Speaker Detection0
Source Free Unsupervised Graph Domain AdaptationCode0
Multi-task Self-distillation for Graph-based Semi-Supervised Learning0
AutoGEL: An Automated Graph Neural Network with Explicit Link InformationCode0
Adaptive Data Augmentation on Temporal Graphs0
Ultrahyperbolic Neural Networks0
Structure-Aware Label Smoothing for Graph Neural Networks0
Contrastive Graph Poisson Networks: Semi-Supervised Learning with Extremely Limited Labels0
p2pGNN: A Decentralized Graph Neural Network for Node Classification in Peer-to-Peer NetworksCode0
Geometric Multimodal Deep Learning with Multi-Scaled Graph Wavelet Convolutional Network0
Network In Graph Neural Network0
StrokeNet: Stroke Assisted and Hierarchical Graph Reasoning Networks0
Graph Neural Networks with Feature and Structure Aware Random Walk0
Transformation of Node to Knowledge Graph Embeddings for Faster Link Prediction in Social NetworksCode0
Neural Class Expression SynthesisCode0
Structure and Features Fusion with Evidential Graph Convolutional Neural Network for Node Classification0
CN-Motifs Perceptive 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
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