Name: Deep Learning @ INAF
Start: 2019-09-16T13:00:00+02:00
End: 2019-09-19T17:00:00+02:00
Location: No location set

Deep Learning @ INAF

from Monday, 16 September 2019 (13:00) to Thursday, 19 September 2019 (17:00)

Monday, 16 September 2019

13:00

13:00 - 14:00

14:00

14:00 - 15:50

15:50 Coffee Break
Coffee Break
15:50 - 16:10

16:10

16:10 - 18:00
Tuesday, 17 September 2019

09:00 Welcome and info
Welcome and info
09:00 - 09:15

09:15

09:15 - 10:50

10:50 Coffee Break
Coffee Break
10:50 - 11:10

11:10

11:10 - 13:00

13:00 Lunch
Lunch
13:00 - 14:20

14:20

14:20 - 16:00

16:00 Coffee Break
Coffee Break
16:00 - 16:20

16:20 Introduction to Deep Learning - tutorial & practice
Introduction to Deep Learning - tutorial & practice
16:20 - 18:00
Wednesday, 18 September 2019

09:10 Data pre & post processing - Parameter Space exploration
Data pre & post processing - Parameter Space exploration
09:10 - 11:00

11:00 Coffee Break
Coffee Break
11:00 - 11:20

11:20 Data exploration - Tutorial & Practice
Data exploration - Tutorial & Practice
11:20 - 13:00

13:00 Lunch
Lunch
13:00 - 14:20
14:20 Data Science and Astrophysics - use case examples
Data Science and Astrophysics - use case examples
14:20 - 16:00
Contributions

14:20 (A few) Deep-Learning applications in Gravitational Lensing - Massimo Meneghetti (Istituto Nazionale di Astrofisica (INAF))

14:45 Machine Learning as a Service - Application of Google Cloud Platform to Machine Learning problems - Marco Landoni (Istituto Nazionale di Astrofisica (INAF))

15:10 A Deep Learning approach for AGILE-GRID GRB Detection - Nicolo' Parmiggiani (Istituto Nazionale di Astrofisica (INAF))

15:35 Discussion
16:00 Coffee Break
Coffee Break
16:00 - 16:20
16:20 Data Science and Astrophysics
Data Science and Astrophysics
16:20 - 18:05
Contributions

16:20 Improving accuracy of Machine Learning algorithms with Feature Selection in the context of particle background discrimination for the AGILE telescope - Leonardo Baroncelli (Istituto Nazionale di Astrofisica (INAF))

16:45 Discovery of new QSOs by means of Canonical Correlation Analysis and photometric catalogs. - Giorgio Calderone (Istituto Nazionale di Astrofisica (INAF))

17:10 A real time approach targeted at buyer prediction, using behaviour classification in Tourism Web Analytics - Massimo Deriu (CRS4)

17:35 Discussion
Thursday, 19 September 2019
09:00
09:00 - 11:00
Contributions

09:00 IBM deep learning - Eleonora Picca (IBM)

10:00 Amazon Web Services - SageMaker platform - Federico d'Alessio (Amazon Web Services - Solution Architect)
11:00 Coffee Break
Coffee Break
11:00 - 11:20
11:20
11:20 - 12:20
Contributions

11:20 Demystifying Deep Learning: A Practical Approach in MATLAB - Giuseppe Ridino (MathWorks)
12:20 General discussion, in-depth insights by the audience with respect to commercial service proposals, practical examples of use
General discussion, in-depth insights by the audience with respect to commercial service proposals, practical examples of use
12:20 - 13:20

13:20 Lunch
Lunch
13:20 - 14:40

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