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 501550 of 1860 papers

TitleStatusHype
GraphFL: A Federated Learning Framework for Semi-Supervised Node Classification on Graphs0
Empty Category Detection using Path Features and Distributed Case Frames0
GraphFM: Improving Large-Scale GNN Training via Feature Momentum0
Edge2Node: Reducing Edge Prediction to Node Classification0
EC-LDA : Label Distribution Inference Attack against Federated Graph Learning with Embedding Compression0
A Process for the Evaluation of Node Embedding Methods in the Context of Node Classification0
Graph Memory Learning: Imitating Lifelong Remembering and Forgetting of Brain Networks0
Graph Mining under Data scarcity0
GraphENS: Neighbor-Aware Ego Network Synthesis for Class-Imbalanced Node Classification0
Graph-FCN for image semantic segmentation0
Graphfool: Targeted Label Adversarial Attack on Graph Embedding0
Dynamic Stacked Generalization for Node Classification on Networks0
Dynamic Spiking Framework for Graph Neural Networks0
Breaking the Entanglement of Homophily and Heterophily in Semi-supervised Node Classification0
Graph Decoupling Attention Markov Networks for Semi-supervised Graph Node Classification0
Active Discovery of Network Roles for Predicting the Classes of Network Nodes0
Each Graph is a New Language: Graph Learning with LLMs0
Graph Embedding with Hierarchical Attentive Membership0
Dynamic Joint Variational Graph Autoencoders0
Boosting Graph Neural Networks via Adaptive Knowledge Distillation0
Dynamic Graph Node Classification via Time Augmentation0
Dynamic Graph Embedding via LSTM History Tracking0
Graph Decipher: A transparent dual-attention graph neural network to understand the message-passing mechanism for the node classification0
Graph Embedding with Rich Information through Heterogeneous Network0
Unsupervised Graph Embedding via Adaptive Graph Learning0
DynACPD Embedding Algorithm for Prediction Tasks in Dynamic Networks0
Node-Time Conditional Prompt Learning In Dynamic Graphs0
Bonsai: Gradient-free Graph Condensation for Node Classification0
DyG-Mamba: Continuous State Space Modeling on Dynamic Graphs0
DVE: Dynamic Variational Embeddings with Applications in Recommender Systems0
Adversarial Attacks on Deep Graph Matching0
Dual Node and Edge Fairness-Aware Graph Partition0
Graph Convolution: A High-Order and Adaptive Approach0
DualHGNN: A Dual Hypergraph Neural Network for Semi-Supervised Node Classification based on Multi-View Learning and Density Awareness0
Dual GNNs: Graph Neural Network Learning with Limited Supervision0
Blockchain Phishing Scam Detection via Multi-channel Graph Classification0
BLIS-Net: Classifying and Analyzing Signals on Graphs0
Graph CNN for Moving Object Detection in Complex Environments from Unseen Videos0
Label Inference Attacks against Node-level Vertical Federated GNNs0
Graph Clustering with Graph Neural Networks0
Graph Coarsening with Message-Passing Guarantees0
GraphGAN: Generating Graphs via Random Walks0
Graph Neural Networks for Binary Programming0
Document Network Projection in Pretrained Word Embedding Space0
Adversarial Active Learning based Heterogeneous Graph Neural Network for Fake News Detection0
Distribution Consistency based Self-Training for Graph Neural Networks with Sparse Labels0
Distributional Signals for Node Classification in Graph Neural Networks0
Adversarial Attack on Hierarchical Graph Pooling Neural Networks0
Graph-Based Uncertainty-Aware Self-Training with Stochastic Node Labeling0
Distributed Representation of Subgraphs0
Show:102550
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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
5GGCMAccuracy74.2Unverified
6GEMAccuracy74.2Unverified
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