8 citations · 14 across the 8 of their papers we have counts for
4 papers · 1 filter
DeepSurveySim: Simulation Software and Benchmark Challenges for Astronomical Observation Scheduling
Maggie Voetberg, Brian Nord
Modern astronomical surveys have multiple competing scientific goals. Optimizing the observation schedule for these goals presents significant computational and theoretical challen…
Self-Driving Telescopes: Autonomous Scheduling of Astronomical Observation Campaigns with Offline Reinforcement Learning
Franco Terranova, M. Voetberg, Brian Nord +1
Modern astronomical experiments are designed to achieve multiple scientific goals, from studies of galaxy evolution to cosmic acceleration. These goals require data of many differe…
Domain Adaptation for Measurements of Strong Gravitational Lenses
Paxson Swierc, Megan Zhao, Aleksandra Ćiprijanović +1
Upcoming surveys are predicted to discover galaxy-scale strong lenses on the order of , making deep learning methods necessary in lensing data analysis. Currently, there is i…
Domain Adaptive Graph Neural Networks for Constraining Cosmological Parameters Across Multiple Data Sets
Andrea Roncoli, Aleksandra Ćiprijanović, Maggie Voetberg +2
Deep learning models have been shown to outperform methods that rely on summary statistics, like the power spectrum, in extracting information from complex cosmological data sets.…