https://github.com/borisbolliet/scatteringtransformtutorials
Tutorials to learn the amazing scattering transform
https://github.com/borisbolliet/scatteringtransformtutorials
Last synced: 6 months ago
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Tutorials to learn the amazing scattering transform
- Host: GitHub
- URL: https://github.com/borisbolliet/scatteringtransformtutorials
- Owner: borisbolliet
- Created: 2024-11-17T13:50:37.000Z (11 months ago)
- Default Branch: main
- Last Pushed: 2024-11-17T14:03:55.000Z (11 months ago)
- Last Synced: 2024-11-17T14:44:29.277Z (11 months ago)
- Language: Jupyter Notebook
- Size: 0 Bytes
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# ScatteringTransformTutorials
Current tutorials include:
- [learning_scattering_transforms_1d](https://github.com/borisbolliet/ScatteringTransformTutorials/blob/main/learning_scattering_transforms_1d.ipynb)
First, watch
- [Stéphane Mallat 1: Mathematical Mysteries of Deep Neural Networks](https://www.youtube.com/watch?v=0wRItoujFTA),
- [Stéphane Mallat 2: Mathematical Mysteries of Deep Neural Networks](https://www.youtube.com/watch?v=kZkjb52zh5k).
Slides are stored here ([part 1](https://github.com/borisbolliet/ScatteringTransformTutorials/blob/main/CadixCours2016_partA.pdf), [part 2](https://github.com/borisbolliet/ScatteringTransformTutorials/blob/main/CadixCours2016_partB.pdf)).
Then, study these tutorial notebooks to learn about the amazing scattering transform.
Seminal references include:
- [Mallat (2012)](https://arxiv.org/abs/1101.2286) [signal processing, functional analysis]
- [Bruna & Mallat (2012)](https://arxiv.org/abs/1203.1513) [signal processing, image recognition]
- [Anden & Mallat (2014)](https://arxiv.org/pdf/1304.6763) [signal processing, audio classification]
- [Allys et al (2019)](https://arxiv.org/abs/1905.01372) [astrophysics]
- [Regaldo-Saint Blancard et al (2021)](https://arxiv.org/abs/2102.03160) [astrophysics]
- [Morel et al (2022)](https://arxiv.org/abs/2204.10177) [finance]
- [Cheng et al (2023)](https://arxiv.org/pdf/2306.17210) [physics]
Very useful material include the PhD thesis of
- [Irène Waldspurger (2015)](https://theses.hal.science/tel-01770221v1/file/Waldspurger-2015-These.pdf)
- [Vincent Lonstalent (2017)](https://theses.hal.science/tel-01559667/file/LOSTANLEN_2017_diffusion.pdf)
Solves and builds upon tutorials found in:
- [kymatio](https://www.kymat.io)
- [cyrusvahidi/scat1d-tutorial](https://github.com/cyrusvahidi/scat1d-tutorial)
- [SihaoCheng/scattering_transform](https://github.com/SihaoCheng/scattering_transform)
- [RudyMorel/scattering_spectra](https://github.com/RudyMorel/scattering_spectra)
Run on GPUs, if you can.
Useful ressource: [deeplearning-math.github.io](https://deeplearning-math.github.io)