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 13511400 of 1860 papers

TitleStatusHype
Memory Augmented Design of Graph Neural Networks0
Graph-Graph Similarity Network0
VECoDeR - Variational Embeddings for Community Detection and Node Representation0
Simple Spectral Graph ConvolutionCode1
NODE-SELECT: A FLEXIBLE GRAPH NEURAL NETWORK BASED ON REALISTIC PROPAGATION SCHEME0
Collective Robustness Certificates0
Global Node Attentions via Adaptive Spectral Filters0
Hard Masking for Explaining Graph Neural Networks0
Adaptive Graph Diffusion NetworksCode1
Bayesian Graph Neural Network for Fast identification of critical nodes in Uncertain Complex Networks0
Semi-Supervised Node Classification on Graphs: Markov Random Fields vs. Graph Neural Networks0
Unifying Homophily and Heterophily Network Transformation via Motifs0
A pipeline for fair comparison of graph neural networks in node classification tasksCode1
An Experimental Study of the Transferability of Spectral Graph NetworksCode0
A Generalization of Transformer Networks to GraphsCode1
Edge Entropy as an Indicator of the Effectiveness of GNNs over CNNs for Node Classification0
A Deep Graph Neural Networks Architecture Design: From Global Pyramid-like Shrinkage Skeleton to Local Topology Link Rewiring0
Understanding graph embedding methods and their applications0
Rethinking the Promotion Brought by Contrastive Learning to Semi-Supervised Node Classification0
LSCALE: Latent Space Clustering-Based Active Learning for Node ClassificationCode0
Blindfolded Attackers Still Threatening: Strict Black-Box Adversarial Attacks on Graphs0
Pair-view Unsupervised Graph Representation Learning0
I-GCN: Robust Graph Convolutional Network via Influence Mechanism0
GraphFL: A Federated Learning Framework for Semi-Supervised Node Classification on Graphs0
NCGNN: Node-Level Capsule Graph Neural Network for Semisupervised Classification0
Unsupervised Adversarially-Robust Representation Learning on Graphs0
Learning Node Representations from Noisy Graph Structures0
Graph Stochastic Neural Networks for Semi-supervised LearningCode1
Unsupervised Joint k-node Graph Representations with Compositional Energy-Based Models0
Adversarial Attacks on Deep Graph Matching0
Graph Random Neural Networks for Semi-Supervised Learning on GraphsCode1
A graph similarity for deep learning0
Unsupervised Constrained Community Detection via Self-Expressive Graph Neural NetworkCode1
Cyclic Label Propagation for Graph Semi-supervised Learning0
AutoGraph: Automated Graph Neural Network0
Revisiting graph neural networks and distance encoding from a practical viewCode0
GNNLens: A Visual Analytics Approach for Prediction Error Diagnosis of Graph Neural Networks0
Learning to Drop: Robust Graph Neural Network via Topological DenoisingCode1
Two-stage Training of Graph Neural Networks for Graph ClassificationCode1
Adversarial Context Aware Network Embeddings for Textual Networks0
GAIN: Graph Attention & Interaction Network for Inductive Semi-Supervised Learning over Large-scale Graphs0
GAGE: Geometry Preserving Attributed Graph Embeddings0
Neural Extractive Summarization with Hierarchical Attentive Heterogeneous Graph Network0
Hyperbolic Graph Embedding with Enhanced Semi-Implicit Variational InferenceCode0
On the Impact of Communities on Semi-supervised Classification Using Graph Neural NetworksCode0
Labeling Trick: A Theory of Using Graph Neural Networks for Multi-Node Representation LearningCode0
GripNet: Graph Information Propagation on Supergraph for Heterogeneous GraphsCode1
Geometric Scattering Attention NetworksCode0
Graph Contrastive Learning with Adaptive AugmentationCode1
Deperturbation of Online Social Networks via Bayesian Label TransitionCode0
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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