4 papers
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 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.…
WavPool: A New Block for Deep Neural Networks
Samuel D. McDermott, M. Voetberg, Brian Nord
Modern deep neural networks comprise many operational layers, such as dense or convolutional layers, which are often collected into blocks. In this work, we introduce a new, wavele…