191 citations
- Stanford UniversityUS3 papers
- University of ChicagoUS3 papers
- University of Wisconsin–MadisonUS3 papers
- Fermi National Accelerator LaboratoryUS2 papers
- Kavli Institute for Particle Astrophysics and CosmologyUS2 papers
- SLAC National Accelerator LaboratoryUS2 papers
- University College LondonGB2 papers
- University of Illinois Urbana-ChampaignUS2 papers
- Archéologie et Histoire Ancienne : Méditerranée – EuropeFR1 paper
- Australian Astronomical ObservatoryAU1 paper
- Australian Astronomical OpticsAU1 paper
- Center for Astrophysics Harvard & SmithsonianUS1 paper
5 papers
Gender Bias in Generative AI-assisted Recruitment Processes
Martina Ullasci, Marco Rondina, Riccardo Coppola +1
In recent years, generative artificial intelligence (GenAI) systems have assumed increasingly crucial roles in selection processes, personnel recruitment and analysis of candidates…
A branching model for intergenerational telomere length dynamics
Athanasios Benetos, Olivier Coudray, Anne Gégout-Petit +3
We build and study an individual based model of the telomere length's evolution in a population across multiple generations. This model is a continuous time typed branching process…
DeepZipper: A Novel Deep Learning Architecture for Lensed Supernovae Identification
Robert Morgan, B. Nord, K. Bechtol +48
Large-scale astronomical surveys have the potential to capture data on large numbers of strongly gravitationally lensed supernovae (LSNe). To facilitate timely analysis and spectro…
lenstronomy II: A gravitational lensing software ecosystem
Simon Birrer, Anowar J. Shajib, Daniel Gilman +18
lenstronomy is an Astropy-affiliated Python package for gravitational lensing simulations and analyses. lenstronomy was introduced by Birrer and Amara (2018) and is based on the li…
deeplenstronomy: A dataset simulation package for strong gravitational lensing
Robert Morgan, Brian Nord, Simon Birrer +2
Automated searches for strong gravitational lensing in optical imaging survey datasets often employ machine learning and deep learning approaches. These techniques require more exa…