| From Data to Software to Science with the Rubin Observatory LSST K Breivik, AJ Connolly, KE Ford, M Jurić, R Mandelbaum, AA Miller, ... arXiv preprint arXiv:2208.02781, 2022 | 4 | 2022 |
| Latent Stochastic Differential Equations for Modeling Quasar Variability and Inferring Black Hole Properties J Fagin, JW Park, H Best, JHH Chan, KES Ford, MJ Graham, VA Villar, ... arXiv preprint arXiv:2304.04277, 2023 | 3 | 2023 |
| Resolving the vicinity of supermassive black holes with gravitational microlensing H Best, J Fagin, G Vernardos, M O'Dowd arXiv preprint arXiv:2210.10500, 2022 | 1 | 2022 |
| Measuring the Substructure Mass Power Spectrum of 23 SLACS Strong Galaxy-Galaxy Lenses with Convolutional Neural Networks J Fagin, G Vernardos, G Tsagkatakis, Y Pantazis, AJ Shajib, M O'Dowd arXiv preprint arXiv:2403.13881, 2024 | | 2024 |
| LenSiam: Self-Supervised Learning on Strong Gravitational Lens Images PW Chang, KW Huang, J Fagin, JHH Chan, JYY Lin arXiv preprint arXiv:2311.10100, 2023 | | 2023 |
| The Pitch and Electric Field Corrections to the Anomalous Muon Spin Precession Frequency for the Muon g-2 Experiment T Barrett, A Chapelain, D Rubin, J Fagin, J Mott, Muon g-2 Collaboration APS April Meeting Abstracts 2021, E20. 007, 2021 | | 2021 |
| Augmentation Matters: Representation Learning for Strong Gravitational Lensing KW Huang, PW Chang, J Fagin, JHH Chan, JYY Lin | | |
