Name: Machine Learning for High Energy Physics - a mini course
Start: 2019-02-04T09:00:00+01:00
End: 2019-02-05T17:45:00+01:00
Location: University of Zurich, Campus Irchel

Machine Learning for High Energy Physics - a mini course

from Monday 4 February 2019 (09:00) to Tuesday 5 February 2019 (17:45)
University of Zurich, Campus Irchel (Y15-G-60)

: Sessions

: Talks

: Breaks

4 Feb 2019

5 Feb 2019

09:00	Registration
09:30	Welcome - Ben Kilminster (Universitaet Zuerich (CH))
09:35	Introduction - Thea Aarrestad (Universitaet Zuerich (CH)) ML4HEP.pdf
09:45	Basics of neural networks and training - Gregor Kasieczka (Hamburg University (DE)) DeepLearning_Zurich_ML4HEP.pdf
10:45	--- Coffee break ---
11:00	Convolutional networks - Gregor Kasieczka (Hamburg University (DE))

09:30	Systematic Uncertainties and Learning from Data - Gregor Kasieczka (Hamburg University (DE)) (Y16-G-15) Slides
10:45	--- Coffee break ---
11:00	Generative Networks and Understanding network decisions - Gregor Kasieczka (Hamburg University (DE)) (Y16-G-15)

12:15	--- Lunch break ---
14:00	Recurrent architectures - Gregor Kasieczka (Hamburg University (DE))
15:00	--- Break ---
15:15	Combining Physics and Deep Learning - Gregor Kasieczka (Hamburg University (DE))
16:30	--- Coffee break ---
17:00	Invited evening talk: Machine Learning for HL-LHC - Jennifer Ngadiuba (CERN) (15-G-60) Ngadiuba_ZurichMLWorkshop2019.pdf

12:00	--- Lunch break ---
14:00	Hands-on - Gregor Kasieczka (Hamburg University (DE)) DeepLearning_ML4HEP_Exercise.pdf Leaderboard Upload Target
15:15	Hands-on - Gregor Kasieczka (Hamburg University (DE))
16:30	--- Coffee break ---
17:00	Scaling up TensorFlow on Accelerators - Marvin Ritter (Google AI)

Choose timezone