DES science portal: Computing photometric redshifts. - Julia Gschwend; A. Carnero Rossel; Ricardo Ogando; Angelo Fausti Neto; Marcio A. G. Maia; Luiz Nicolaci da Costa; Marcos Lima; Paulo S. S. Pellegrini; Riccardo Campisano; C. Singulani; C. Adean; Christophe O. Benoist; et al. (Astron. Comput., 2018)

DES science portal: Creating science-ready catalogs. - Angelo Fausti Neto; Luiz Nicolaci da Costa; Aurelio Carnero Rosell; Julia Gschwend; R. L. C. Ogando; Flavia Sobreira; Marcio A. G. Maia; Basillio X. Santiago; Rogério Rosenfeld; C. Singulani; C. Adean; L. D. P. Nunes; et al. (Astron. Comput., 2018)

Optical follow-up of gravitational wave triggers with DECam during the first two LIGO/VIRGO observing runs. - Ken Herner; James Annis; Dillon Brout; Marcelle Soares-Santos; Richard Kessler; Masao Sako; Ray F. Butler; Zoheyr Doctor; Antonella Palmese; Sahar Allam; Douglas L. Tucker; Flavia Sobreira; et al. (Astron. Comput., 2020)

Machine Learning for Searching the Dark Energy Survey for Trans-Neptunian Objects. - Ben Henghes; Ofer Lahav; David W. Gerdes; E. Lin; Robert Morgan; Timothy M. C. Abbott; Michel Aguena; Sahar Allam; James Annis; Santiago Ávila; Emmanuel Bertin; David D. Brooks; et al. (CoRR, 2020)

A machine learning approach to galaxy properties: Joint redshift - stellar mass probability distributions with Random Forest. - Sunil Mucesh; William G. Hartley; Antonella Palmese; Ofer Lahav; L. Whiteway; A. Amon; Keith C. Bechtol; Gary M. Bernstein; Aurelio Carnero Rosell; Matias Carrasco Kind; A. Choi; K. Eckert; et al. (CoRR, 2020)

LSTM and CNN application for core-collapse supernova search in gravitational wave real data. - Alberto Iess; Elena Cuoco; Filip Morawski; Constantina Nicolaou; Ofer Lahav (CoRR, 2023)

Nature versus nurture in galaxy formation: the effect of environment on star formation with causal machine learning. - Sunil Mucesh; William G. Hartley; Ciarán M. Gilligan-Lee; Ofer Lahav (CoRR, 2024)

Finding Pegasus: Enhancing Unsupervised Anomaly Detection in High-Dimensional Data using a Manifold-Based Approach. - R. P. Nathan; Nikolaos Nikolaou; Ofer Lahav (CoRR, 2025)