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| == Workshop 2018: Machine Learning and Numerical Simulations | == 1st Workshop: Machine Learning and Numerical Simulations == |
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| ||<tablewidth=""" tablestyle="" & quot; & amp; quot; & amp; amp; quot; & amp; amp; amp; quot; & amp; amp; amp; amp; quot; & amp; amp; amp; amp; amp; quot; & amp; amp; amp; amp; amp; amp; quot; & amp; amp; amp; amp; amp; amp; amp; quot; & amp; amp; amp; amp; amp; amp; amp; amp; quot; & amp; amp; amp; amp; amp; amp; amp; amp; amp; quot; & amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; quot; & amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; quot; & amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; quot; & amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; quot; & amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; quot; 200px& amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; quot& amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; quot; ; & amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; quot& amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; quot& amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; quot; ; & amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; quot& amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; quot& amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; quot; ; & amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; quot& amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; quot& amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; quot; ; & amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; quot& amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; quot& amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; quot; ; & amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; quot& amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; quot& amp; amp; amp; amp; amp; amp; amp; amp; amp; quot; ; & amp; amp; amp; amp; amp; amp; amp; amp; amp; amp; quot& amp; amp; amp; amp; amp; amp; amp; amp; amp; quot& amp; amp; amp; amp; amp; amp; amp; amp; quot; ; & amp; amp; amp; amp; amp; amp; amp; amp; amp; quot& amp; amp; amp; amp; amp; amp; amp; amp; quot& amp; amp; amp; amp; amp; amp; amp; quot; ; & amp; amp; amp; amp; amp; amp; amp; amp; quot& amp; amp; amp; amp; amp; amp; amp; quot& amp; amp; amp; amp; amp; amp; quot; ; & amp; amp; amp; amp; amp; amp; amp; quot& amp; amp; amp; amp; amp; amp; quot& amp; amp; amp; amp; amp; quot; ; & amp; amp; amp; amp; amp; amp; quot& amp; amp; amp; amp; amp; quot& amp; amp; amp; amp; quot; ; & amp; amp; amp; amp; amp; quot& amp; amp; amp; amp; quot& amp; amp; amp; quot; ; & amp; amp; amp; amp; quot& amp; amp; amp; quot& amp; amp; quot; ; & amp; amp; amp; quot& amp; amp; quot& amp; quot; ; & amp; amp; quot& amp; quot& quot; ; & amp; quot& quot" ;&quot"">Name ||Presentation Title || ||Eric JULLO ||Machine Learning in Euclid Strong Lensing Working Group || #||Annie Zavagno ||Big Data, Machine Learning and Star Formation properties || #||Annie Zavagno ||Numerical simulations of ionized regions || ||Ignasi Pérez Ràfols ||TBD - Introduction to Machine Learning on Python || ||Kasia Malek ||Unsupervised machine learning algorithms for galaxy classification (based mostly on VIPERS sample) || ||Christian Surace ||Maybe (status of french oppotunities in ML) || ||Morgane Cousin || Review on semi-analytical models for galaxy formation || || ... || |
|| Time || Talk || || 9:45-10:00 || Coffee || || 10:00-10:25|| Ignasi Pérez Ràfols || Introduction to Machine Learning on Python || || 10:30-10:55|| Kasia Malek || Unsupervised machine learning algorithms for galaxy classification (based mostly on VIPERS sample) || || 11:00-11:25|| Annie Zavagno ? || Big Data, Machine Learning and Star Formation properties || || 11:30-11:55|| Eric Jullo || Machine Learning in Euclid Strong Lensing Working Group || || 12:00-14:00|| Buffet lunch || || 14:00-14:25|| Stéphane Arnouts ? || Deep learning technique for photo-z || || 14:30-14:55|| Christian Surace || Status of French opportunities in ML || || 15:00-15:25|| Morgane Cousin || Review on semi-analytical models for galaxy formation || || 15:30-15:55|| Arturo Nunez || Hydro-dynamical-cosmological simulations of Milky Way sized spiral galaxies with the zoom-in technique || 16:00-16:30|| Discussion || |
Transverse Science Workshops
This is a series of workshops organised within the GECO group. The workshops are focussed on specific topics that are transverse to all research activities within the group.
1st Workshop: Machine Learning and Numerical Simulations
The first workshop of this series will be about Machine Learning and Numerical Simulations and will take pace at LAM on the 16th of April 2018.
List of proposed presentations:
Time |
Talk |
|
9:45-10:00 |
Coffee |
|
10:00-10:25 |
Ignasi Pérez Ràfols |
Introduction to Machine Learning on Python |
10:30-10:55 |
Kasia Malek |
Unsupervised machine learning algorithms for galaxy classification (based mostly on VIPERS sample) |
11:00-11:25 |
Annie Zavagno ? |
Big Data, Machine Learning and Star Formation properties |
11:30-11:55 |
Eric Jullo |
Machine Learning in Euclid Strong Lensing Working Group |
12:00-14:00 |
Buffet lunch |
|
14:00-14:25 |
Stéphane Arnouts ? |
Deep learning technique for photo-z |
14:30-14:55 |
Christian Surace |
Status of French opportunities in ML |
15:00-15:25 |
Morgane Cousin |
Review on semi-analytical models for galaxy formation |
|| 15:30-15:55|| Arturo Nunez || Hydro-dynamical-cosmological simulations of Milky Way sized spiral galaxies with the zoom-in technique
16:00-16:30 |
Discussion |