Big Data Science in Astroparticle Research - Workshop

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Sessions*

Arrive

Coffee

Open Data, Data Centers, Computing Technology

Discussion on perspectives and common efforts

Depart

Deep Learning

Lunch

Conference Dinner

Tutorial: Information Field Theory: Ford Room

Deep Learning

Beginners Tutorial Deep Learning

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Contributions*

A Deep Neural Network for Pixel-Level Electromagnetic Particle Identification in the MicroBooNE Lar TPC (tbc) (in session "Deep Learning")

Application of Deep Learning methods to analysis of Imaging Atmospheric Cherenkov Telescopes data (in session "Deep Learning")

Autonomous Physics-Inspired Feature Engineering (in session "Deep Learning")

Bayesian reconstruction of the cosmic Dark Matter velocity field (in session "Deep Learning")

Beginners Tutorial Deep Networks: Introduction (in session "Beginners Tutorial Deep Learning")

Cascade Reconstruction in IceCube using Generative Networks (in session "Deep Learning")

Challenges and Opportunities of Digital Transformation in Fundamental Research on Universe and Matter (in session "Open Data, Data Centers, Computing Technology")

Contracting alignment patterns of mixed composition nuclei (in session "Deep Learning")

CTA Software and Science Data Management (in session "Open Data, Data Centers, Computing Technology")

Data engineering for joint analysis of different astroparticle data in KRAD project (in session "Open Data, Data Centers, Computing Technology")

Data Science in Astroparticle Physics (in session "Deep Learning")

Deep Learning and Mathematical Modeling: Taking the Best out of Both Worlds (in session "Deep Learning")

Deep learning techniques applied to the physics of extensive air showers (in session "Deep Learning")

Deep Neural Networks for Energy and Position Reconstruction in EXO-200 (in session "Deep Learning")

Event classification in Compton-Pair telescopes using Deep Learning Techniques (in session "Deep Learning")

Exploring Antarctic Ice Properties Using Generative Neural Networks (in session "Deep Learning")

Exploring Optical Properties of Antarctic Ice with IceCube Using Gradient Descent (in session "Deep Learning")

Inspection of the AIXNET network for air shower reconstruction (in session "Deep Learning")

Introduction tutorial to Information Field Theory and Exercises (in session "Tutorial: Information Field Theory: Ford Room")

Introduction tutorial to Information Field Theory and Exercises (in session "Tutorial: Information Field Theory: Ford Room")

Open high-level data and tools for gamma-ray astronomy (in session "Open Data, Data Centers, Computing Technology")

Precise simulation of electromagnetic calorimeter showers using a Wasserstein Generative Adversarial Network (in session "Deep Learning")

Reconstruction of air-shower radio pulses from real Tunka-Rex background with autoencoder network (in session "Deep Learning")

Recovery of Radio Signals from Cosmic Ray Induced Air Showers with Deep Learning (in session "Deep Learning")

The ESCAPE project and the EOSC (in session "Open Data, Data Centers, Computing Technology")

Welcome and organizational matters (in session "Tutorial: Information Field Theory: Ford Room")

Welcome at the RWTH Aachen University (in session "Deep Learning")

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Events scheduled on*

2/18/19

2/19/19

2/20/19

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