8 citations · 14 across the 8 of their papers we have counts for
5 papers · 1 filter
Population-level Dark Energy Constraints from Strong Gravitational Lensing using Simulation-Based Inference
Sreevani Jarugula, Brian Nord, Abhijith Gandrakota +1
In this work, we present a scalable approach for inferring the dark energy equation-of-state parameter () from a population of strong gravitational lens images using Simulation-…
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…
Petabytes to Science
Amanda E. Bauer, Eric C. Bellm, Adam S. Bolton +24
A Kavli foundation sponsored workshop on the theme \emph{Petabytes to Science} was held 12 to 14 of February 2019 in Las Vegas. The aim of the this workshop was to di…