Méthodes IA / Data Science pour la physique

mardi 29 janv. 2019, 09:30 → 15:30 Europe/Paris

CH201 (Saint Charles)

09:30 → 09:45 Présentation des participants

Orateur: Magali Muraglia

09:45 → 10:15 Big data & machine learning en physique des particules

Orateur: Yann Coadou (CPPM Marseille)

MethodesIADataSciencePhysiqueAMU190129.pdf

10:15 → 10:45 Les activités deep learning en cosmologie au CPPM

Orateur: Johanna Pasquet (CPPM)

talk_pasquet.pdf

10:45 → 11:00 Pause

11:00 → 11:30 The GyroKinetic DataBase (GKDB) project : a community tool for code benchmarks and building fast turbulent transport models

Orateur: Yann Camenen (PIIM)

Y_CAMENEN_GKDB_IA_2019.pdf

11:30 → 12:00 Data Science for the prediction of particule transport induced by energetic particle modes

Orateur: David Zarzoso (PIIM)

12:00 → 12:30 Detection of Turbulence Driven Magnetic Islands in Tokamaks: Towards Neural Network?

Orateur: Myriam Hamed (PIIM, IRFM, CEA)

Slides_MHD_Hamed.pdf

12:30 → 14:00 Déjeuner

14:00 → 14:30 PoPe method for Verification of codes and Reduction of models

Orateur: Thomas Cartier-Michaud (M2P2)

TCM_IA_Data_29_01_19_Cartier_Michaud.pdf

14:30 → 15:00 PoPe verification of VOICE 1D-1V multispecies kinetics

Orateur: Philippe Ghendrih (IRFM, CEA)

2019-01-29_Ghendrih_Philippe.pdf

15:00 → 15:30 Data analysis strategies with GYSELA

Orateur: Elisabetta Caschera (IRFM, CEA)

ECaschera_29_01_2019.pptx