Kymatio: Scattering Transforms in Python
This provides a practical tool for researchers and practitioners in signal processing and machine learning, though it is incremental as it focuses on software implementation rather than new algorithmic advances.
The authors tackled the need for an accessible and efficient implementation of the wavelet scattering transform by developing Kymatio, a Python package that supports 1D, 2D, and 3D transforms with GPU acceleration, offering significant speed improvements over CPU implementations.
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/