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 201250 of 1860 papers

TitleStatusHype
Task-Adaptive Few-shot Node ClassificationCode1
Understanding convolution on graphs via energiesCode1
GraphFramEx: Towards Systematic Evaluation of Explainability Methods for Graph Neural NetworksCode1
Sheaf Neural Networks with Connection LaplaciansCode1
Long Range Graph BenchmarkCode1
DiffWire: Inductive Graph Rewiring via the Lovász BoundCode1
CLNode: Curriculum Learning for Node ClassificationCode1
ACMP: Allen-Cahn Message Passing for Graph Neural Networks with Particle Phase TransitionCode1
NAGphormer: A Tokenized Graph Transformer for Node Classification in Large GraphsCode1
Neo-GNNs: Neighborhood Overlap-aware Graph Neural Networks for Link PredictionCode1
I'm Me, We're Us, and I'm Us: Tri-directional Contrastive Learning on HypergraphsCode1
Label-Enhanced Graph Neural Network for Semi-supervised Node ClassificationCode1
Automatic Relation-aware Graph Network ProliferationCode1
Geometer: Graph Few-Shot Class-Incremental Learning via Prototype RepresentationCode1
EvenNet: Ignoring Odd-Hop Neighbors Improves Robustness of Graph Neural NetworksCode1
Compressing Deep Graph Neural Networks via Adversarial Knowledge DistillationCode1
Recipe2Vec: Multi-modal Recipe Representation Learning with Graph Neural NetworksCode1
Heterformer: Transformer-based Deep Node Representation Learning on Heterogeneous Text-Rich NetworksCode1
Finding Global Homophily in Graph Neural Networks When Meeting HeterophilyCode1
RoSA: A Robust Self-Aligned Framework for Node-Node Graph Contrastive LearningCode1
Neural Structured Prediction for Inductive Node ClassificationCode1
Graph Ordering Attention NetworksCode1
GraFN: Semi-Supervised Node Classification on Graph with Few Labels via Non-Parametric Distribution AssignmentCode1
Node Representation Learning in Graph via Node-to-Neighbourhood Mutual Information MaximizationCode1
BNS-GCN: Efficient Full-Graph Training of Graph Convolutional Networks with Partition-Parallelism and Random Boundary Node SamplingCode1
Exploiting Neighbor Effect: Conv-Agnostic GNNs Framework for Graphs with HeterophilyCode1
View-Consistent Heterogeneous Network on Graphs With Few Labeled NodesCode1
GRAND+: Scalable Graph Random Neural NetworksCode1
R-GCN: The R Could Stand for RandomCode1
GAP: Differentially Private Graph Neural Networks with Aggregation PerturbationCode1
Graph Attention RetrospectiveCode1
MuMiN: A Large-Scale Multilingual Multimodal Fact-Checked Misinformation Social Network DatasetCode1
Graph Masked Autoencoders with TransformersCode1
Random Laplacian Features for Learning with Hyperbolic SpaceCode1
Neural Sheaf Diffusion: A Topological Perspective on Heterophily and Oversmoothing in GNNsCode1
MarkovGNN: Graph Neural Networks on Markov DiffusionCode1
Convolutional Neural Networks on Graphs with Chebyshev Approximation, RevisitedCode1
Graph Coloring with Physics-Inspired Graph Neural NetworksCode1
When Do Flat Minima Optimizers Work?Code1
Graph Representation Learning via Aggregation EnhancementCode1
FedGCN: Convergence-Communication Tradeoffs in Federated Training of Graph Convolutional NetworksCode1
Unsupervised Graph Poisoning Attack via Contrastive Loss Back-propagationCode1
Decoupling the Depth and Scope of Graph Neural NetworksCode1
Towards Unsupervised Deep Graph Structure LearningCode1
MGAE: Masked Autoencoders for Self-Supervised Learning on GraphsCode1
Towards Similarity-Aware Time-Series ClassificationCode1
Hypergraph-Induced Semantic Tuplet Loss for Deep Metric LearningCode1
Motif Graph Neural NetworkCode1
Deformable Graph Convolutional NetworksCode1
Lifelong Learning on Evolving Graphs Under the Constraints of Imbalanced Classes and New ClassesCode1
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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
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
4Truncated KrylovAccuracy81.7Unverified
5SuperGAT MXAccuracy81.7Unverified
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