Kymatio: Scattering Transforms in Python

Autor: Andreux, Mathieu, Angles, Tomás, Exarchakis, Georgios, Leonarduzzi, Roberto, Rochette, Gaspar, Thiry, Louis, Zarka, John, Mallat, Stéphane, andén, Joakim, Belilovsky, Eugene, Bruna, Joan, Lostanlen, Vincent, Chaudhary, Muawiz, Hirn, Matthew J., Oyallon, Edouard, Zhang, Sixin, Cella, Carmine, Eickenberg, Michael
Přispěvatelé: Owkin France, Département d'informatique - ENS Paris (DI-ENS), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS), Flatiron Institute, Simons Foundation, Chaire Sciences des données, Collège de France (CdF (institution)), Department of Mathematics [Sweden] (KTH), Stockholm University, Montreal Institute for Learning Algorithms [Montréal] (MILA), Centre de Recherches Mathématiques [Montréal] (CRM), Université de Montréal (UdeM)-Université de Montréal (UdeM), New York University [New York] (NYU), NYU System (NYU), Michigan State University [Traverse City], Michigan State University System, Machine Learning and Information Access (MLIA), LIP6, Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Peking University [Beijing], Center for New Music and Audio Technologies (CNMAT), Oyallon, Edouard, Département d'informatique de l'École normale supérieure (DI-ENS), École normale supérieure - Paris (ENS-PSL), Collège de France - Chaire Sciences des données
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: Journal of Machine Learning Research
Journal of Machine Learning Research, Microtome Publishing, 2020, 21 (60), pp.1-6
Journal of Machine Learning Research, 2020, 21 (60), pp.1-6
ISSN: 1532-4435
1533-7928
Popis: International audience; 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/
Databáze: OpenAIRE