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
Revisiting Graph Convolutional Network on Semi-Supervised Node Classification from an Optimization Perspective0
Revisiting Graph Neural Networks for Link Prediction0
Revisiting Heterophily in Graph Convolution Networks by Learning Representations Across Topological and Feature Spaces0
Revisiting Neighborhood Aggregation in Graph Neural Networks for Node Classification using Statistical Signal Processing0
Revisiting Over-smoothing in Deep GCNs0
RGL: A Simple yet Effective Relation Graph Augmented Prompt-based Tuning Approach for Few-Shot Learning0
RLC-GNN: An Improved Deep Architecture for Spatial-Based Graph Neural Network with Application to Fraud Detection0
NodeSig: Binary Node Embeddings via Random Walk Diffusion0
Robustness Inspired Graph Backdoor Defense0
Robust Subgraph Learning by Monitoring Early Training Representations0
RoCP-GNN: Robust Conformal Prediction for Graph Neural Networks in Node-Classification0
ROG_PL: Robust Open-Set Graph Learning via Region-Based Prototype Learning0
RW-NSGCN: A Robust Approach to Structural Attacks via Negative Sampling0
SA-GDA: Spectral Augmentation for Graph Domain Adaptation0
SAS: A Simple, Accurate and Scalable Node Classification Algorithm0
Scalability Matters: Overcoming Challenges in InstructGLM with Similarity-Degree-Based Sampling0
Scalable Deep Metric Learning on Attributed Graphs0
SearchGCN: Powering Embedding Retrieval by Graph Convolution Networks for E-Commerce Search0
Seastar: vertex-centric programming for graph neural networks0
SEEN: Sharpening Explanations for Graph Neural Networks using Explanations from Neighborhoods0
Select and Calibrate the Low-confidence: Dual-Channel Consistency based Graph Convolutional Networks0
Self-attention Dual Embedding for Graphs with Heterophily0
Self-Directed Learning of Convex Labelings on Graphs0
Self-Explainable Graph Neural Networks for Link Prediction0
Self-Supervised Graph Representation Learning via Global Context Prediction0
Self-supervised Incremental Deep Graph Learning for Ethereum Phishing Scam Detection0
Self-supervised Learning for Heterogeneous Graph via Structure Information based on Metapath0
Self-Supervised Pretraining for Heterogeneous Hypergraph Neural Networks0
SAIL: Self-Augmented Graph Contrastive Learning0
Semantic2Graph: Graph-based Multi-modal Feature Fusion for Action Segmentation in Videos0
Semantic Graph Neural Network with Multi-measure Learning for Semi-supervised Classification0
Semi-Supervised Graph Embedding for Multi-Label Graph Node Classification0
Semi-Supervised Hierarchical Graph Classification0
Semi-Supervised Learning on Graphs Based on Local Label Distributions0
Semi-supervised Network Embedding with Differentiable Deep Quantisation0
Semi-Supervised Node Classification on Graphs: Markov Random Fields vs. Graph Neural Networks0
Semi-Supervised Tensor Factorization for Node Classification in Complex Social Networks0
SF-GNN: Self Filter for Message Lossless Propagation in Deep Graph Neural Network0
SFR-GNN: Simple and Fast Robust GNNs against Structural Attacks0
Sharp Bounds for Poly-GNNs and the Effect of Graph Noise0
Sheaf Hypergraph Networks0
Shedding Light on Problems with Hyperbolic Graph Learning0
Shift-Robust Node Classification via Graph Adversarial Clustering0
Shoestring: Graph-Based Semi-Supervised Classification With Severely Limited Labeled Data0
Signed Graph Neural Networks: A Frequency Perspective0
SignGT: Signed Attention-based Graph Transformer for Graph Representation Learning0
SiGNN: A Spike-induced Graph Neural Network for Dynamic Graph Representation Learning0
Similarity-aware Positive Instance Sampling for Graph Contrastive Pre-training0
Simple Truncated SVD based Model for Node Classification on Heterophilic Graphs0
Simple yet Effective Gradient-Free Graph Convolutional 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
10DifNetAccuracy85.1Unverified
#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