Kymatio: Scattering Transforms in Python
M. Andreux
Tomás Angles
Georgios Exarchakis
R. Leonarduzzi
G. Rochette
L. Thiry
J. Zarka
S. Mallat
Joakim Andén
Eugene Belilovsky
Joan Bruna
Vincent Lostanlen
Muawiz Chaudhary
M. Hirn
Edouard Oyallon
Sixhin Zhang
Carmine-Emanuele Cella
Michael Eickenberg

Abstract
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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