activity
20192026
most citedVEXAS: VISTA EXtension to Auxiliary Surveys -- Data Release 2: Machine-learning based classification of sources in the Southern Hemisphere

9 citations · 16 across the 5 of their papers we have counts for

collaborators

5 papers

astro-ph.IM2026

Euclid Quick Data Release (Q1). AstroVink: A vision transformer approach to find strong gravitational lens systems

Euclid Collaboration, S. H. Vincken, K. Rojas +302

We present AstroVink, a vision transformer classifier designed for automated identification of strong lens candidates in Euclid imaging. We build upon the DINOv2 encoder, fine tune…

astro-ph.GA2026

Euclid Quick Data Release (Q1). The Strong Lensing Discovery Engine F -- Bright and low-redshift strong lenses

Euclid Collaboration, L. R. Ecker, M. Fabricius +346

We present 72 additional galaxy-galaxy strong lenses that complement the sample discovered in the Euclid Quick Release 1 data (63.1 deg^2) of the Strong Lens Discovery Engine (SLDE…

astro-ph.GA2026

Beyond compactness: a structural-dynamical-evolutionary manifold for the stellar-to-dynamical mass ratio in ultra-compact massive galaxies

Chiara Spiniello

Ultra-compact massive galaxies (UCMGs) exhibit elevated stellar-to-dynamical mass ratios when dynamical masses are estimated using standard virial prescriptions. This discrepancy h…

astro-ph.GA2021★ 9 cited

VEXAS: VISTA EXtension to Auxiliary Surveys -- Data Release 2: Machine-learning based classification of sources in the Southern Hemisphere

V. Khramtsov, C. Spiniello, A. Agnello +1

We present the second public data release (DR) of the VISTA EXtension to Auxiliary Surveys (VEXAS), where we classify objects into stars, galaxies and quasars based on an ensemble…

astro-ph.GA2019★ 7 cited

VEXAS: the VISTA EXtension to Auxiliary Surveys -- Data Release 1: the Southern Galactic Hemisphere

C. Spiniello, A. Agnello

We present the first public data release of the VISTA EXtension to Auxiliary Surveys (VEXAS), comprising of 9 cross-matched multi-wavelength photometric catalogs where each object…