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Wiki of the Machine Learning / Deep Learning Pole

INFORMATION WEB PAGE for the ML/DL Pole at CeSAM
This is a selection of some references that may be useful to start or consolidate your knowledge. This information is of course not exhaustive and any suggestions for additions are welcome. If you have any questions, please send an email to

Reference publications

Books & Code Examples

Frameworks to start & to document in ML/DL

Online courses

Next conferences or training workshops

Previous conferences on ML/DL with astrophysical topics

Previous training workshops

Seminars

For the presentations, the slides can be retrieved with the link; the videos can be viewed on https://seminars.lam.fr/#MLDL
  • 12/02/2024 : Anthony Lagain (CEREGE) " Machine Learning applied to large planetary imagery datasets for impact crater detection "
  • 08/01/2024 : Adeline Paiement (LIS) " Physics-informed Deep Neural Network for characterising galaxy morphology " (240108 Paiement)
  • 04/12/2023 : Reda Ait Ouhamed (LAM) " Galaxy redsfhit estimation from multi-band images with Deep Learning " (231204 Reda)
  • 20/11/2023 : Raoul Canameras (MPA-Garching) " Supervised Deep Learning methods for Rubin LSST, lmage classification, mass modeling and photometric redshift prediction " (231120 Canameras)
  • 05/04/2023 : Eric Wulff (CERN) " Hyperparameter Optimization for DL using HPC" (230405 Wulff)
  • 25/03/2022 : François Lanusse (CosmoStat) " Probabilistic Deep Learning for Weak Lensing : from Mass-Mapping to Cosmological Parameter Inference " (https://eiffl.github.io/LAM2022/)
  • 04/05/2021 : Raoul Canameras (MPA-Garching) " Finding and modeling strong gravitational lenses with deep neural networks " (210504 Canameras)
  • 30/03/2021 : Alexandre Boucaud & Hubert Bretonnière (LAC) " FlowVAE: taking control of galaxy image simulations with deep generative networks "
  • 09/03/2021 : Laurent Risser (IMT) " Explainability techniques for black-box decision rules in Machine Learning " (210309 Risser)
  • 11/02/2021 : Sidonie Lefebvre (ONERA/DOTA) " Generative Adversarial Networks (GANs) : concept and application to cloudy sky images synthesis " (210211 Lefevbre)
  • 01/02/2021 : Nicolas Audebert (CNAM) " Hyperspectral remote sensing data analysis using Deep Learning " (210201 Audebert)
  • 18/01/2021 : François-Xavier Dupé (LIS/QARMA) " How Machine Learning can help to automate processing tasks ? An example with image denoising " (210118 Dupe)
  • 11/01/2021 : Julien Wojak (Institut Fresnel) " Deep Learning : focus on auto-encoder as a pre-processing step for classification " (210111 Wojak)

ML/DL pole staff & project implications

Available GPUs computing resources for LAM staff