Identifying Exoplanets with Deep Learning. IV. Removing Stellar Activity Signals from Radial Velocity Measurements Using Neural Networks. - Zoë L. de Beurs; Andrew Vanderburg; Christopher J. Shallue; Xavier Dumusque; Andrew Collier Cameron; Lars A. Buchhave; Rosario Cosentino; Adriano Ghedina; Raphaëlle D. Haywood; Nicholas Langellier; David W. Latham; Mercedes López-Morales; et al. (CoRR, 2020)

Forcing the Network to Use Human Explanations in Its Inference Process. - Javier Viaña; Andrew Vanderburg (NAFIPS, 2023)

Identifying Exoplanets with Deep Learning. V. Improved Light Curve Classification for TESS Full Frame Image Observations. - Evan Tey; Dan Moldovan; Michelle Kunimoto; Chelsea X. Huang; Avi Shporer; Tansu Daylan; Daniel Muthukrishna; Andrew Vanderburg; Anne Dattilo; George R. Ricker; S. Seager (CoRR, 2023)

cecilia: A Machine Learning-Based Pipeline for Measuring Metal Abundances of Helium-rich Polluted White Dwarfs. - Mariona Badenas-Agusti; Javier Viaña; Andrew Vanderburg; Simon Blouin; Patrick Dufour; Siyi Xu; Siyi Sha (CoRR, 2024)

LensNet: Enhancing Real-time Microlensing Event Discovery with Recurrent Neural Networks in the Korea Microlensing Telescope Network. - Javier Viaña; Kyu-Ha Hwang; Zoë L. de Beurs; Jennifer C. Yee; Andrew Vanderburg; Michael D. Albrow; Sun-Ju Chung; Andrew Gould; Cheongho Han; Youn Kil Jung; Yoon-Hyun Ryu; In-Gu Shin; et al. (CoRR, 2025)

A Machine-Learning Compositional Study of Exoplanetary Material Accreted Onto Five Helium-Atmosphere White Dwarfs with cecilia. - Mariona Badenas-Agusti; Siyi Xu; Andrew Vanderburg; Kishalay De; Patrick Dufour; Laura K. Rogers; Susana Hoyos; Simon Blouin; Javier Viaña; Amy Bonsor; Ben Zuckerman (CoRR, 2025)