mlsanityData to 14 Oct 2026

GraphKAN: Enhancing Feature Extraction with Graph Kolmogorov Arnold Networks

arXiv 2406.13597 ↗First posted 19 Jun 2024cs.LG cs.AIcited by 32

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Abstract (arXiv)

Massive number of applications involve data with underlying relationships embedded in non-Euclidean space. Graph neural networks (GNNs) are utilized to extract features by capturing the dependencies within graphs. Despite groundbreaking performances, we argue that Multi-layer perceptrons (MLPs) and fixed activation functions impede the feature extraction due to information loss. Inspired by Kolmogorov Arnold Networks (KANs), we make the first attempt to GNNs with KANs. We discard MLPs and activation functions, and instead used KANs for feature extraction. Experiments demonstrate the effectiveness of GraphKAN, emphasizing the potential of KANs as a powerful tool. Code is available at https://github.com/Ryanfzhang/GraphKan.

Key facts. Cited by 32 papers in the map (data through 14 Oct 2026). Builds on 15 of its 24 references that are in the map. First posted on arXiv 19 Jun 2024.

Builds on

15 of 24 references.

References · 15

  1. 2017Graph Attention Networkscited by 8,923
  2. 2018How Powerful are Graph Neural Networks?cited by 4,393
  3. 2018Graph Neural Networks: A Review of Methods and Applicationscited by 1,576
  4. 2017Neural Collaborative Filteringcited by 1,111
  5. 2019Graph Neural Networks for Social Recommendationcited by 714
  6. 2024KAN: Kolmogorov-Arnold Networkscited by 649
  7. 2016Error bounds for approximations with deep ReLU networkscited by 574
  8. 2015An Introduction to Convolutional Neural Networkscited by 514
  9. 2017Residual Attention Network for Image Classificationcited by 386
  10. 2019Understanding and Improving Layer Normalizationcited by 217
  11. 2018Traffic Graph Convolutional Recurrent Neural Network: A Deep Learning Framework for Network-Scale Traffic Learning and Forecastingcited by 146
  12. 2019Neural Machine Translation: A Review and Surveycited by 100
3 more
  1. 2020Building powerful and equivariant graph neural networks with structural message-passingcited by 97
  2. 2020Model Interpretability through the Lens of Computational Complexitycited by 75
  3. 2017A Capacity Scaling Law for Artificial Neural Networkscited by 7

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 15; 2025: 15; 2026: 2.

32 papers.

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  1. 2024KAN 2.0: Kolmogorov-Arnold Networks Meet Sciencecited by 118
  2. 2024A Survey on Kolmogorov-Arnold Networkcited by 68
  3. 2024KAGNNs: Kolmogorov-Arnold Networks meet Graph Learningcited by 49
  4. 2024On the expressiveness and spectral bias of KANscited by 37
  5. 2024Kolmogorov-Arnold Graph Neural Networkscited by 32
  6. 2024Reduced Effectiveness of Kolmogorov-Arnold Networks on Functions with Noisecited by 17
  7. 2024PointNet with KAN versus PointNet with MLP for 3D Classification and Segmentation of Point Setscited by 15
  8. 2024KAN versus MLP on Irregular or Noisy Functionscited by 7
  9. 2024TransUKAN:Computing-Efficient Hybrid KAN-Transformer for Enhanced Medical Image Segmentationcited by 6
  10. 2025Free-Knots Kolmogorov-Arnold Network: On the Analysis of Spline Knots and Advancing Stabilitycited by 6
  11. 2024KAN we improve on HEP classification tasks? Kolmogorov-Arnold Networks applied to an LHC physics examplecited by 4
  12. 2024Incorporating Arbitrary Matrix Group Equivariance into KANscited by 4
20 more
  1. 2024KAN v.s. MLP for Offline Reinforcement Learningcited by 3
  2. 2025AF-KAN: Activation Function-Based Kolmogorov-Arnold Networks for Efficient Representation Learningcited by 3
  3. 2025Physics-informed KAN PointNet: Deep learning for simultaneous solutions to inverse problems in incompressible flow on numerous irregular geometriescited by 3
  4. 2025Conformalized-KANs: Uncertainty Quantification with Coverage Guarantees for Kolmogorov-Arnold Networks (KANs) in Scientific Machine Learningcited by 3
  5. 2025Interpretable Clinical Classification with Kolmogorov-Arnold Networkscited by 3
  6. 2025Automatic Grid Updates for Kolmogorov-Arnold Networks using Layer Histogramscited by 3
  7. 2024Kolmogorov Arnold Networks in Fraud Detection: Bridging the Gap Between Theory and Practicecited by 2
  8. 2025SFFR: Spatial-Frequency Feature Reconstruction for Multispectral Aerial Object Detectioncited by 2
  9. 2025KAA: Kolmogorov-Arnold Attention for Enhancing Attentive Graph Neural Networkscited by 1
  10. 2025Advancing Out-of-Distribution Detection via Local Neuroplasticitycited by 1
  11. 2025GKAN: Explainable Diagnosis of Alzheimer's Disease Using Graph Neural Network with Kolmogorov-Arnold Networkscited by 1
  12. 2025MLPs and KANs for data-driven learning in physical problems: A performance comparisoncited by 1
  13. 2025Khan-GCL: Kolmogorov-Arnold Network Based Graph Contrastive Learning with Hard Negativescited by 1
  14. 2026Hardware-Oriented Inference Complexity of Kolmogorov-Arnold Networkscited by 1
  15. 2024Efficient Privacy-Preserving KAN Inference Using Homomorphic Encryptioncited by 0
  16. 2024On the Convergence of (Stochastic) Gradient Descent for Kolmogorov--Arnold Networkscited by 0
  17. 2025HKAN: Hierarchical Kolmogorov-Arnold Network without Backpropagationcited by 0
  18. 2025Transferring Social Network Knowledge from Multiple GNN Teachers to Kolmogorov-Arnold Networkscited by 0
  19. 2025Kolmogorov-Arnold graph neural networks for chemically informed prediction tasks on inorganic nanomaterialscited by 0
  20. 2026Singularity Formation: Synergy in Theoretical, Numerical and Machine Learning Approachescited by 0