Big Data Science in Astroparticle Research - HAP Workshop

Session

19 Feb 2018, 14:00

RWTH Aachen University SuperC

Contribution list Timetable

2. Welcome and organizational matters

Prof. Martin Erdmann (RWTH Aachen University)

19/02/2018, 14:00

0. Tutorial Deep Networks: Introduction, Fully-Connected, Convolutional Architectures

Mr. Yannik Rath (RWTH Aachen University)

19/02/2018, 14:15

1. Tutorial on Adversarial Generative Networks, Wasserstein distance

Mr. Jonas Glombitza (RWTH Aachen University)

19/02/2018, 16:15

3. Welcome Message of the Vice-Rector for Research and Structure

Prof. Rudolf Mathar (RWTH Aachen University)

20/02/2018, 09:00

4. DeepJet: jet classification with the CMS experiment

Dr. Markus Stoye (CERN)

20/02/2018, 09:15

6. Application of machine learning methods to H.E.S.S. data analysis

Dr. Idan Shilon (ECAP University Erlangen)

20/02/2018, 10:00

26. Event Reconstruction in IceCube using Deep Learning Techniques

Mr. Mirco Huennefeld (TU Dortmund)

20/02/2018, 10:20

24. Efficient Similarity Search and Analysis

Dr. Christian Beecks

20/02/2018, 11:10

9. Generating and refining particle detector simulations using the Wasserstein distance in adversarial networks

Mr. Lukas Geiger (RWTH Aachen University)

20/02/2018, 11:55

5. HexagDLy - Hexagonal Convolutions with PyTorch

Mr. Tim Lukas Holch (Humboldt University Berlin)

20/02/2018, 12:15

22. Deep machine learning implementation in FPGA

Dr. Michele Caselle (KIT), Mr. Weijia WANG

20/02/2018, 12:35

8. Investigating deep convolutional autoencoders to mitigate systematic differences between data and simulations

Dr. Stefan Geißelsöder (ECAP, FAU Erlangen)

20/02/2018, 16:30

10. Using Deep Learning to optimise a SUSY search at CMS

Dr. Adam Elwood (DESY Hamburg)

20/02/2018, 16:45