8 citations · 18 across the 8 of their papers we have counts for
3 papers · 1 filter
VST-SMASH: the VST Survey of Mass Assembly and Structural Hierarchy
Crescenzo Tortora, Rossella Ragusa, Massimiliano Gatto +21
The VLT Survey Telescope Survey of Mass Assembly and Structural Hierarchy (VST-SMASH) aims to detect tidal features and remnants around very nearby galaxies, a unique and essential…
Inferring redshift and galaxy properties via a multi-task neural net with probabilistic outputs: An application to simulated MOONS spectra
Michele Ginolfi, Filippo Mannucci, Francesco Belfiore +11
The era of large-scale astronomical surveys demands innovative approaches for rapid and accurate analysis of extensive spectral data, and a promising direction in which to address…
Inferring stellar parameters and their uncertainties from high-resolution spectroscopy using invertible neural networks
Nils Candebat, Giuseppe Germano Sacco, Laura Magrini +3
Context: New spectroscopic surveys will increase the number of astronomical objects requiring characterization by over tenfold.. Machine learning tools are required to address this…