Big Data Science in Astroparticle Research - HAP Workshop

Session

Deep Learning

Feb 19, 2018, 2:00 PM

RWTH Aachen University SuperC

2. Welcome and organizational matters

Prof. Martin Erdmann (RWTH Aachen University)

2/19/18, 2:00 PM

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

Mr Yannik Rath (RWTH Aachen University)

2/19/18, 2:15 PM

1. Tutorial on Adversarial Generative Networks, Wasserstein distance

Mr Jonas Glombitza (RWTH Aachen University)

2/19/18, 4:15 PM

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

Prof. Rudolf Mathar (RWTH Aachen University)

2/20/18, 9:00 AM

4. DeepJet: jet classification with the CMS experiment

Dr Markus Stoye (CERN)

2/20/18, 9:15 AM

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

Dr Idan Shilon (ECAP University Erlangen)

2/20/18, 10:00 AM

26. Event Reconstruction in IceCube using Deep Learning Techniques

Mr Mirco Huennefeld (TU Dortmund)

2/20/18, 10:20 AM

24. Efficient Similarity Search and Analysis

Dr Christian Beecks

2/20/18, 11:10 AM

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

Mr Lukas Geiger (RWTH Aachen University)

2/20/18, 11:55 AM

5. HexagDLy - Hexagonal Convolutions with PyTorch

Mr Tim Lukas Holch (Humboldt University Berlin)

2/20/18, 12:15 PM

22. Deep machine learning implementation in FPGA

Dr Michele Caselle (KIT), Mr Weijia WANG

2/20/18, 12:35 PM

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

Dr Stefan Geißelsöder (ECAP, FAU Erlangen)

2/20/18, 4:30 PM

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

Dr Adam Elwood (DESY Hamburg)

2/20/18, 4:45 PM