mlsanityData to 14 Oct 2026

Kymatio: Scattering Transforms in Python

arXiv 1812.11214 ↗First posted 28 Dec 2018cs.LG cs.CV cs.SDcited by 58

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Abstract (arXiv)

The wavelet scattering transform is an invariant signal representation suitable for many signal processing and machine learning applications. We present the Kymatio software package, an easy-to-use, high-performance Python implementation of the scattering transform in 1D, 2D, and 3D that is compatible with modern deep learning frameworks. All transforms may be executed on a GPU (in addition to CPU), offering a considerable speed up over CPU implementations. The package also has a small memory footprint, resulting inefficient memory usage. The source code, documentation, and examples are available undera BSD license at https://www.kymat.io/

Key facts. Cited by 58 papers in the map (data through 14 Oct 2026). First posted on arXiv 28 Dec 2018.

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Citing papers per year: 2021: 12; 2022: 11; 2023: 9; 2024: 9; 2025: 5; 2026: 12.

58 papers.

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  1. 2021Learning curves of generic features maps for realistic datasets with a teacher-student modelcited by 126
  2. 2022Learning Operators with Coupled Attentioncited by 90
  3. 2022NOMAD: Nonlinear Manifold Decoders for Operator Learningcited by 83
  4. 2021Fully Learnable Deep Wavelet Transform for Unsupervised Monitoring of High-Frequency Time Seriescited by 29
  5. 2022Gaussian Universality of Perceptrons with Random Labelscited by 26
  6. 2023Are Gaussian data all you need? Extents and limits of universality in high-dimensional generalized linear estimationcited by 26
  7. 2021Parametric Scattering Networkscited by 16
  8. 2021A Bayesian neural network predicts the dissolution of compact planetary systemscited by 15
  9. 2021ScatSimCLR: self-supervised contrastive learning with pretext task regularization for small-scale datasetscited by 9
  10. 2021InQSS: a speech intelligibility and quality assessment model using a multi-task learning networkcited by 7
  11. 2021Equivariant Wavelets: Fast Rotation and Translation Invariant Wavelet Scattering Transformscited by 6
  12. 2021Phase Collapse in Neural Networkscited by 5
38 more
  1. 2023Riesz feature representation: scale equivariant scattering network for classification taskscited by 4
  2. 2023Divergences in Color Perception between Deep Neural Networks and Humanscited by 4
  3. 2024Space-scale Exploration of the Poor Reliability of Deep Learning Models: the Case of the Remote Sensing of Rooftop Photovoltaic Systemscited by 4
  4. 2024Tackling the Accuracy-Interpretability Trade-off in a Hierarchy of Machine Learning Models for the Prediction of Extreme Heatwavescited by 4
  5. 2022Monogenic Wavelet Scattering Network for Texture Image Classificationcited by 3
  6. 2022Physics-assisted Generative Adversarial Network for X-Ray Tomographycited by 3
  7. 2022TRUST-LAPSE: An Explainable and Actionable Mistrust Scoring Framework for Model Monitoringcited by 3
  8. 2023Heart Murmur and Abnormal PCG Detection via Wavelet Scattering Transform & a 1D-CNNcited by 3
  9. 2024WhaleNet: a Novel Deep Learning Architecture for Marine Mammals Vocalizations on Watkins Marine Mammal Sound Databasecited by 3
  10. 2026WaveScat: Wavelet Scattering Front-Ends with Self-Supervised Features for Speech Deepfake Detectioncited by 3
  11. 2023Mesostructures: Beyond Spectrogram Loss in Differentiable Time-Frequency Analysiscited by 2
  12. 2023Wavelets Beat Monkeys at Adversarial Robustnesscited by 2
  13. 2025Wavelet Scattering Transform and Fourier Representation for Offline Detection of Malicious Clients in Federated Learningcited by 2
  14. 2022Efficient Hybrid Network: Inducting Scattering Featurescited by 1
  15. 2022Differentiable Time-Frequency Scattering on GPUcited by 1
  16. 2022Multi-Resolution Online Deterministic Annealing: A Hierarchical and Progressive Learning Architecturecited by 1
  17. 2023Perceptual-Neural-Physical Sound Matchingcited by 1
  18. 2023MV-MR: multi-views and multi-representations for self-supervised learning and knowledge distillationcited by 1
  19. 2024Integrating Graph Neural Networks with Scattering Transform for Anomaly Detectioncited by 1
  20. 2024Simulation-based inference with scattering representations: scattering is all you needcited by 1
  21. 2024TRENDy: Temporal Regression of Effective Nonlinear Dynamicscited by 1
  22. 2025The Maximal Overlap Discrete Wavelet Scattering Transform and Its Application in Classification Taskscited by 1
  23. 2025VDW-GNNs: Vector diffusion wavelets for geometric graph neural networkscited by 1
  24. 2026Scale-Equivariant Generative Forecasting: Weight-Tied Dilated Convolutions, Wavelet Scattering Inputs, and Spectral-Consistency Training for Self-Similar Time Seriescited by 1
  25. 2021Dynamic Texture Recognition via Nuclear Distances on Kernelized Scattering Histogram Spacescited by 0
  26. 2021Reference-based Texture transfer for Single Image Super-resolution of Magnetic Resonance imagescited by 0
  27. 2021CXR-Net: An Artificial Intelligence Pipeline for Quick Covid-19 Screening of Chest X-Rayscited by 0
  28. 2021Towards the One Learning Algorithm Hypothesis: A System-theoretic Approachcited by 0
  29. 2022Radar-based Materials Classification Using Deep Wavelet Scattering Transform: A Comparison of Centimeter vs. Millimeter Wave Unitscited by 0
  30. 2022Attention-Based Scattering Network for Satellite Imagerycited by 0
  31. 2023Mallat Scattering Transformation based surrogate for MagnetoHydroDynamicscited by 0
  32. 2024Mean-Field Microcanonical Gradient Descentcited by 0
  33. 2024Hyperspectral Reconstruction of Skin Through Fusion of Scattering Transform Featurescited by 0
  34. 2024Enhanced Wavelet Scattering Network for image inpainting detectioncited by 0
  35. 2025Explainable and Class-Revealing Signal Feature Extraction via Scattering Transform and Constrained Zeroth-Order Optimizationcited by 0
  36. 2025Simulation-informed deep learning for enhanced SWOT observations of fine-scale ocean dynamicscited by 0
  37. 2026Scattering Transform for Auditory Attention Decodingcited by 0
  38. 2026Bayesian Scattering: A Principled Baseline for Uncertainty on Image Datacited by 0

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