Name: Deep Learning in the Natural Sciences
Start: 2019-02-28T08:45:00+01:00
End: 2019-03-01T18:00:00+01:00
Location: Hamburg

Deep Learning in the Natural Sciences

from Thursday 28 February 2019 (08:45) to Friday 1 March 2019 (18:00)

Monday 25 February 2019
Tuesday 26 February 2019
Wednesday 27 February 2019
Thursday 28 February 2019
10:00 Pre-Workshop introduction and arrival
Pre-Workshop introduction and arrival
10:00 - 13:00
Contributions

10:00 Registration & Sign-Up

10:15 Deep Learning Basics I - Gregor Kasieczka (Hamburg University (DE))

11:15 Deep Learning Basics II - Gregor Kasieczka (Hamburg University (DE))
12:00 Lunch
Lunch
12:00 - 13:00
13:00 Talks I
Talks I
13:00 - 15:00
Contributions

13:00 Opening - Gregor Kasieczka (Hamburg University (DE)) Marcus Brueggen

13:20 Collision Course: Particle Physics as a Machine-Learning Testbed - Jesse Thaler (MIT)

14:00 Machine Learning Techniques in Cosmological Simulation - Claudio Gheller

14:40 Low-dose X-ray Imaging with Deep Neural Networks - Xiaogang Yang
15:00 Coffee Break
Coffee Break
15:00 - 15:40
15:40 Talks II
Talks II
15:40 - 18:00
Contributions

15:40 Machine Learning Techniques in Astroparticle Physics - Dominik Elsaesser

16:20 Rise of the Tagging Machines - Tilman Plehn (Heidelberg University) Tilman Plehn

17:00 Machine Learning for Diffractive Imaging and Crystallography - Filipe Maia
Friday 1 March 2019
09:00 Talks III
Talks III
09:00 - 11:00
Contributions

09:00 Deep Learning in Particle and Astroparticle Physics - Martin Erdmann (Rheinisch Westfaelische Tech. Hoch. (DE))

09:40 A metric for collider events - Patrick Komiske (Massachusetts Institute of Technology)

10:00 Radio Galaxy Classifications with Deep Learning - Vesna Lukic

10:20 Particle identification on the DAMPE experiment - David Francois Droz (Universite de Geneve (CH))

10:40 Machine learning with augmentation for boosting di-Higgs searches at the LHC - Won Sang Cho (Seoul National University)
11:00 Coffee Break
Coffee Break
11:00 - 11:30
11:30 Talks IV
Talks IV
11:30 - 13:30
Contributions

11:30 Application of Generative Models to Natural Science - Fedor Ratnikov Fedor Ratnikov (Yandex School of Data Analysis (RU))

12:10 Towards data-driven particle physics classifiers - Eric Metodiev (Massachusetts Institute of Technology)

12:30 Autoencoding New Physics - Jennifer Thompson (ITP Heidelberg) Jennifer Thompson (ITP Heidelberg)

12:50 CNN Classification of X-ray Selected Clusters - Matej Kosiba

13:10 Closing Discussion - Peter Schleper (Hamburg University (DE))

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