33 citations · 91 across the 17 of their papers we have counts for
3 papers · 1 filter
Unsupervised Domain Adaptation for Constraining Star Formation Histories
Sankalp Gilda, Antoine de Mathelin, Sabine Bellstedt +1
The prevalent paradigm of machine learning today is to use past observations to predict future ones. What if, however, we are interested in knowing the past given the present? This…
Uncertainty-Aware Learning for Improvements in Image Quality of the Canada-France-Hawaii Telescope
Sankalp Gilda, Stark C. Draper, Sebastien Fabbro +6
We leverage state-of-the-art machine learning methods and a decade's worth of archival data from CFHT to predict observatory image quality (IQ) from environmental conditions and ob…
{\sc mirkwood:} Fast and Accurate SED Modeling Using Machine Learning
Sankalp Gilda, Sidney Lower, Desika Narayanan
Traditional spectral energy distribution (SED) fitting codes used to derive galaxy physical properties are often uncertain at the factor of a few level owing to uncertainties in ga…