5 citations · 9 across the 3 of their papers we have counts for
3 papers
astro-ph.IM2021
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…
astro-ph.IM2020★ 5 cited
Astronomical Image Quality Prediction based on Environmental and Telescope Operating Conditions
Sankalp Gilda, Yuan-Sen Ting, Kanoa Withington +6
Intelligent scheduling of the sequence of scientific exposures taken at ground-based astronomical observatories is massively challenging. Observing time is over-subscribed and atmo…
cs.RO2019★ 4 cited
Learning to Manipulate Object Collections Using Grounded State Representations
Matthew Wilson, Tucker Hermans
We propose a method for sim-to-real robot learning which exploits simulator state information in a way that scales to many objects. We first train a pair of encoder networks to cap…