Big Techday 23: Generative Data Calibrates the Sky [EN] - Dr Tamás Varga, LMU Munich

Generative Data Calibrates the Sky

Dark energy - the accelerating expansion of the Universe - is one of the key unsolved mysteries of physics today. A prominent way to understand cosmic expansion and growth is through vast surveys of the night sky where hundreds of millions of galaxies are photographed and catalogued, searching for subtle correlations in their positions and shapes. At LMU and the Max Planck for extraterrestrial Physics we develop powerful machine learning and Bayesian inference pipelines to extract insight from raw data. But calibrating and validating these tools cannot be done with real observations alone! Instead we build fair and statistically valid generative synthetic data models to characterise and forecast performance for yet to be seen astrophysical measurements. In my talk I will outline the key machine learning methods which power our work within the Dark Energy Survey (DES) and the Legacy Survey of Space and Time (LSST) and highlight their real world applications which could bring business value.

About the speaker
Dr. Tamás Varga: Dr. Tamás Norbert Varga is a research scientist at LMU and Max Planck Institute for extraterrestrial Physics where he is responsible for designing the generative synthetic data pipeline which will help power the largest cosmological survey ever constructed, the Legacy Survey of Space and Time (LSST). Cosmology provides a unique insight into a world where generative data tools have already been ubiquitous for years, and where the focus has therefore shifted from generation to ensuring the certification and statistical validity of AI methods. As a member of both LSST and the Dark Energy Survey (DES), Tamás worked at the frontier of data intensive cosmology research, in which he received his PhD in 2020 at LMU.

Видео Big Techday 23: Generative Data Calibrates the Sky [EN] - Dr Tamás Varga, LMU Munich канала TNG Technology Consulting GmbH