mlsanityData to 7 Oct 2026

Graph Wavelet Neural Network

arXiv 1904.07785 ↗First posted 12 Apr 2019cs.LG stat.MLcited by 131

Not on the map. Why?

Abstract (arXiv)

We present graph wavelet neural network (GWNN), a novel graph convolutional neural network (CNN), leveraging graph wavelet transform to address the shortcomings of previous spectral graph CNN methods that depend on graph Fourier transform. Different from graph Fourier transform, graph wavelet transform can be obtained via a fast algorithm without requiring matrix eigendecomposition with high computational cost. Moreover, graph wavelets are sparse and localized in vertex domain, offering high efficiency and good interpretability for graph convolution. The proposed GWNN significantly outperforms previous spectral graph CNNs in the task of graph-based semi-supervised classification on three benchmark datasets: Cora, Citeseer and Pubmed.

Key facts. Cited by 131 papers in the map (data through 7 Oct 2026). First posted on arXiv 12 Apr 2019.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 36; 2022: 23; 2023: 27; 2024: 23; 2025: 16; 2026: 6.

131 papers.

Sort:

By area:

  1. 2021Beyond Low-frequency Information in Graph Convolutional Networkscited by 361
  2. 2021Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networkscited by 219
  3. 2021BernNet: Learning Arbitrary Graph Spectral Filters via Bernstein Approximationcited by 195
  4. 2022Rethinking Graph Neural Networks for Anomaly Detectioncited by 185
  5. 2021Interpreting and Unifying Graph Neural Networks with An Optimization Frameworkcited by 131
  6. 2023Specformer: Spectral Graph Neural Networks Meet Transformerscited by 102
  7. 2022Wavelet neural operator: a neural operator for parametric partial differential equationscited by 77
  8. 2021Dissecting the Diffusion Process in Linear Graph Convolutional Networkscited by 58
  9. 2021How Framelets Enhance Graph Neural Networkscited by 46
  10. 2021Single Node Injection Attack against Graph Neural Networkscited by 45
  11. 2021SDGNN: Learning Node Representation for Signed Directed Networkscited by 44
  12. 2022Spatio-Temporal Graph Few-Shot Learning with Cross-City Knowledge Transfercited by 43
38 more
  1. 2024Wavelet Diffusion Neural Operatorcited by 28
  2. 2021On the Universality of Graph Neural Networks on Large Random Graphscited by 26
  3. 2023A Survey on Spectral Graph Neural Networkscited by 26
  4. 2021LT-OCF: Learnable-Time ODE-based Collaborative Filteringcited by 21
  5. 2021Multiresolution Equivariant Graph Variational Autoencodercited by 20
  6. 2022Complete the Missing Half: Augmenting Aggregation Filtering with Diversification for Graph Convolutional Neural Networkscited by 19
  7. 2021Beyond Low-Pass Filters: Adaptive Feature Propagation on Graphscited by 18
  8. 2021Bridging the Gap between Spatial and Spectral Domains: A Unified Framework for Graph Neural Networkscited by 18
  9. 2021Signed Bipartite Graph Neural Networkscited by 18
  10. 2022Overcoming Oversmoothness in Graph Convolutional Networks via Hybrid Scattering Networkscited by 18
  11. 2022Efficient Integration of Multi-Order Dynamics and Internal Dynamics in Stock Movement Predictioncited by 18
  12. 2024Spectral Invariant Learning for Dynamic Graphs under Distribution Shiftscited by 18
  13. 2022TIDE: Time Derivative Diffusion for Deep Learning on Graphscited by 17
  14. 2022Node-oriented Spectral Filtering for Graph Neural Networkscited by 17
  15. 2021Graph Neural Networks: Methods, Applications, and Opportunitiescited by 16
  16. 2021Deconvolutional Networks on Graph Datacited by 16
  17. 2021Beyond Low-pass Filtering: Graph Convolutional Networks with Automatic Filteringcited by 14
  18. 2023Unifying over-smoothing and over-squashing in graph neural networks: A physics informed approach and beyondcited by 13
  19. 2022Handling Missing Data via Max-Entropy Regularized Graph Autoencodercited by 12
  20. 2021Adaptive Gaussian Processes on Graphs via Spectral Graph Waveletscited by 11
  21. 2022Adversarial Camouflage for Node Injection Attack on Graphscited by 11
  22. 2022MM-GNN: Mix-Moment Graph Neural Network towards Modeling Neighborhood Feature Distributioncited by 11
  23. 2022A Magnetic Framelet-Based Convolutional Neural Network for Directed Graphscited by 11
  24. 2024Pre-Training and Prompting for Few-Shot Node Classification on Text-Attributed Graphscited by 11
  25. 2022Generalized energy and gradient flow via graph frameletscited by 10
  26. 2022Learnable Spectral Wavelets on Dynamic Graphs to Capture Global Interactionscited by 10
  27. 2023Company-as-Tribe: Company Financial Risk Assessment on Tribe-Style Graph with Hierarchical Graph Neural Networkscited by 10
  28. 2023Predicting the Silent Majority on Graphs: Knowledge Transferable Graph Neural Networkcited by 10
  29. 2023Bridged-GNN: Knowledge Bridge Learning for Effective Knowledge Transfercited by 10
  30. 2025Time Series Analysis in Frequency Domain: A Survey of Open Challenges, Opportunities and Benchmarkscited by 10
  31. 2023On Manipulating Signals of User-Item Graph: A Jacobi Polynomial-based Graph Collaborative Filteringcited by 9
  32. 2021Graph Denoising with Framelet Regularizercited by 8
  33. 2023A Survey on Graph Classification and Link Prediction based on GNNcited by 8
  34. 2022Unsupervised Network Embedding Beyond Homophilycited by 7
  35. 2023PointWavelet: Learning in Spectral Domain for 3D Point Cloud Analysiscited by 7
  36. 2024Counterfactual Data Augmentation with Denoising Diffusion for Graph Anomaly Detectioncited by 7
  37. 2021Graph Neural Networks With Lifting-based Adaptive Graph Waveletscited by 6
  38. 2021Geometric Multimodal Deep Learning with Multi-Scaled Graph Wavelet Convolutional Networkcited by 6

50 most cited of 131 All 131 (JSON)