Particle/Astro-Machine Learning Seminar

Probabilistic Neural Networks for Cosmology

Abstract:
While our understanding of the Universe's composition and formation has
advanced in the last two decades, fundamental questions persist. The
nature of the majority of the Universe, comprising 27% Dark Matter and
68% Dark Energy, remains unknown. To unveil these mysteries, astronomers
are constructing ambitious telescopes and sky surveys. LSST and Euclid
will soon come online, surveying vast portions of the sky with
unprecedented depth.
To deal with this volume of data, machine learning methods are planned

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