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arxiv: 1812.11214 · v3 · pith:INJNGSX7 · submitted 2018-12-28 · cs.LG · cs.CV· cs.SD· eess.AS· stat.ML

Kymatio: Scattering Transforms in Python

Mathieu Andreux , Tom\'as Angles , Georgios Exarchakis , Roberto Leonarduzzi , Gaspar Rochette , Louis Thiry , John Zarka , St\'ephane Mallat
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Joakim and\'en Eugene Belilovsky Joan Bruna Vincent Lostanlen Muawiz Chaudhary Matthew J. Hirn Edouard Oyallon Sixin Zhang Carmine Cella Michael Eickenberg
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classification cs.LG cs.CVcs.SDeess.ASstat.ML
keywords scatteringkymatiolearningmemorypackagepythonsignaltransform
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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/

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