5 citations · 9 across the 5 of their papers we have counts for
6 papers
Primordial non-Gaussianity -- Fast simulations and persistent summary statistics
Juan Calles, Gabriella Contardo, Jorge Noreña +2
We investigate the sensitivity of topological and traditional summary statistics to primordial non-Gaussianity (PNG) using two suites of simulations. First, we introduce a new simu…
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…
Cosmology with Persistent Homology: Parameter Inference via Machine Learning
Juan Calles, Jacky H. T. Yip, Gabriella Contardo +3
Building upon [2308.02636], we investigate the constraining power of persistent homology on cosmological parameters and primordial non-Gaussianity in a likelihood-free inference pi…
A Data-Driven Search For Mid-Infrared Excesses Among Five Million Main-Sequence FGK Stars
Gabriella Contardo, David W. Hogg
Stellar infrared excesses can indicate various phenomena of interest, from protoplanetary disks to debris disks, or (more speculatively) techno-signatures along the lines of Dyson…