26.09, 14:30–18:30 (Europe/Berlin), ESA Ost 120
Sprache: English
Chair: Tim Ruhe, Universität Dortmund
The development of machine learning algorithms has emerged as a driving force for advancements in astroparticle physics and astronomy. The future of this development can be expected to hold nothing less than groundbreaking scientific discoveries. The involved data analysis tasks, e.g. particle reconstruction and ML-based deconvolution, require a diverse set of algorithms, such as ensemble classifiers, regression, unsupervised learning, imbalanced learning and various types of neural networks. The efficient generation of large amounts of annotated examples in simulations is a key characteristic of the field and of its largest challenges. This interdisciplinary workshop will bring together leading experts from Computer Science, astroparticle physics and astronomy, to present and discuss recent developments at the intersection of these fast evolving fields. The ultimate goal of this workshop is to foster collaborations across multiple disciplines to further advance all fields involved.
Weitere Infos unter: https://sfb876.tu-dortmund.de/ml.astro/index.html
Keynotes
14:30 – 15:00 Katharina Morik, TU Dortmund University: Machine Learning for Astroparticle Physics
15:00 – 15:30 Daniel Nieto, Universidad Complutense de Madrid: Applications of Machine Learning to Gamma-Ray Astronomy
15:30 – 16:00 Alejandro Moreo, Instituto di Szienza e Tecnologie dell’Informazione: Quantification
16:00 – 16:30 break
Contributed Talks
16:30 – 16:50 Mirko Bunse, TU Dortmund University: Unification of Algorithms for Quantification and Unfolding
16:50 – 17:10 Janis Kummer, Center for Data and Computing in Natural Sciences (CDCS)/ Universität Hamburg: Radio Galaxy Classification with wGAN-Supported Augmentation
17:10 – 17:30 Dmitry Malyshev, Erlangen Centre for Astroparticle Physics: To split or not to split classes of gamma-ray sources?
17:30 – 17:50 Shreyas Kalvankar, K. K. Wagh Institute of Engineering Education and Research: Astronomical Image colorization and up-scaling with Conditional Generative Adversarial Networks
17:50 – 18:10 Pranav Sampathkumar, Karlsruhe Institute for Technology: Sequential networks for cosmic ray simulations
18:10 – 18:30 Jigar Bhanderi, University of Erlangen-Nurenberg: Calculation of the Photon Flux in a Photo-Multiplier Tube with Deep Learning