2 citations · 2 across the 3 of their papers we have counts for
4 papers
Dark Matter profiles of "in silico" galaxies: deep learning inference
Martín de los Rios, Serafina Di Gioia, Fabio Iocco +1
Machine learning has the potential to improve the reconstruction of the dark matter profile of galaxies with respect to traditional methods, like rotation curves. We demonstrate on…
Rotary Masked Autoencoders are Versatile Learners
Uros Zivanovic, Serafina Di Gioia, Andre Scaffidi +3
Applying Transformers to irregular time-series typically requires specializations to their baseline architecture, which can result in additional computational overhead and increase…
On the effects of parameters on galaxy properties in CAMELS and the predictability of
Gabriella Contardo, Roberto Trotta, Serafina Di Gioia +2
Recent analyses of cosmological hydrodynamic simulations from CAMELS have shown that machine learning models can predict the parameter describing the total matter content of the un…
Detecting Localized Density Anomalies in Multivariate Data via Coin-Flip Statistics
Sebastian Springer, Andre Scaffidi, Maximilian Autenrieth +4
Detecting localized differences between two samples is a central task in scientific data analysis, required for the identification of signal events, regime changes, or model mismat…