18 citations · 41 across the 7 of their papers we have counts for
7 papers
The promise of self-supervised and active learning for Strong Lens discovery: Astronomaly applied to KiDS
Margherita Grespan, Aprajita Verma, Michelle Lochner +3
Strong gravitational lenses (SGLs) are rare systems whose discovery currently relies primarily on supervised machine learning methods trained on large simulated datasets. We presen…
Automated quasar continuum estimation using neural networks: a comparative study of deep-learning architectures
Francesco Pistis, Michele Fumagalli, Matteo Fossati +13
Context. Ongoing and upcoming large spectroscopic surveys are drastically increasing the number of observed quasar spectra, requiring the development of fast and accurate automated…
Investigating the Redshift Evolution of Lensing Galaxy Density Slopes via Model-Independent Distance Ratios
Shuaibo Geng, Margherita Grespan, Hareesh Thuruthipilly +3
Strong lensing systems, expected to be abundantly discovered by next-generation surveys, offer a powerful tool for studying cosmology and galaxy evolution. The connection between g…
TEGLIE: Transformer encoders as strong gravitational lens finders in KiDS
Margherita Grespan, Hareesh Thuruthipilly, Agnieszka Pollo +3
We apply a state-of-the-art transformer algorithm to 221 deg of the Kilo Degree Survey (KiDS) to search for new strong gravitational lenses (SGL). We test four transformer enco…
Probing massive gravitons in with lensed gravitational waves
Vipin Kumar Sharma, Sreekanth Harikumar, Margherita Grespan +2
We investigate the novel features of gravitational wave solutions in gravity under proper gauge considerations in the shifted Ricci scalar background curvature ().…
Astronomaly at scale: searching for anomalies amongst 4 million galaxies
Verlon Etsebeth, Michelle Lochner, Mike Walmsley +1
Modern astronomical surveys are producing datasets of unprecedented size and richness, increasing the potential for high-impact scientific discovery. This possibility, coupled with…
Transformers as Strong Lens Detectors- From Simulation to Surveys
Hareesh Thuruthipilly, Margherita Grespan, Adam Zadrożny
With the upcoming large-scale surveys like LSST, we expect to find approximately strong gravitational lenses among data of many orders of magnitude larger. In this scenario,…