JMLR Journal 2020 Journal Article
Kymatio: Scattering Transforms in Python
- Mathieu Andreux
- Tomás Angles
- Georgios Exarchakis
- Roberto Leonarduzzi
- Gaspar Rochette
- Louis Thiry
- John Zarka
- Stéphane Mallat
The wavelet scattering transform is an invariant and stable 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, including PyTorch and TensorFlow/Keras. The transforms are implemented on both CPUs and GPUs, the latter offering a significant speedup over the former. The package also has a small memory footprint. Source code, documentation, and examples are available under a BSD license at https://www.kymat.io. [abs] [ pdf ][ bib ] [ code ] © JMLR 2020. ( edit, beta )