35 citations · 35 across the 2 of their papers we have counts for
2 papers
astro-ph.CO2022★ 35 cited
A Deep Learning Approach to Infer Galaxy Cluster Masses from Planck Compton parameter maps
Daniel de Andres, Weiguang Cui, Florian Ruppin +8
Galaxy clusters are useful laboratories to investigate the evolution of the Universe, and accurately measuring their total masses allows us to constrain important cosmological para…
stat.ML2022
Advancing Reacting Flow Simulations with Data-Driven Models
Kamila Zdybał, Giuseppe D'Alessio, Gianmarco Aversano +4
The use of machine learning algorithms to predict behaviors of complex systems is booming. However, the key to an effective use of machine learning tools in multi-physics problems,…