arXiv (Cornell University) · 2018 · 77 citations · 11 references
ComputingComputer ScienceHigh-performance ComputingComputer GraphicsComputer VisionMachine LearningDeep LearningDigital Signal ProcessingRepresentation LearningScattering AnalysisScattering TheorySignal ProcessingComputation SpeedDeep Learning On GpusInvariant Feature RepresentationInvariant Representation LearningMemory Footprint ReductionScattering ModelsScattering Transformation
The wavelet scattering transform is an invariant signal representation\nsuitable for many signal processing and machine learning applications. We\npresent the Kymatio software package, an easy-to-use, high-performance Python\nimplementation of the scattering transform in 1D, 2D, and 3D that is compatible\nwith modern deep learning frameworks. All transforms may be executed on a GPU\n(in addition to CPU), offering a considerable speed up over CPU\nimplementations. The package also has a small memory footprint, resulting\ninefficient memory usage. The source code, documentation, and examples are\navailable undera BSD license at https://www.kymat.io/\n
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Scikit-learn: Machine Learning in Python
Fabián Pedregosa, Gaël Varoquaux, Alexandre Gramfort et al. · arXiv (Cornell University) · 2012 · 63.7K citations · Full text
Stéphane Mallat · Communications on Pure and Applied Mathematics · 2012 · 1K citations
Joakim Andén, Stéphane Mallat · IEEE Transactions on Signal Processing · 2014 · 653 citations · Full text
Computing, Musicology, Acoustics +16