71 citations · 72 across the 4 of their papers we have counts for
4 papers
ExoMiner++ 2.0: Vetting TESS Full-Frame Image Transit Signals
Miguel J. S. Martinho, Hamed Valizadegan, Jon M. Jenkins +4
The Transiting Exoplanet Survey Satellite (TESS) Full-Frame Images (FFIs) provide photometric time series for millions of stars, enabling transit searches beyond the limited set of…
Foundation Models for Astrobiology: Paper I -- Workshop and Overview
Ryan Felton, Caleb Scharf, Stuart Bartlett +18
Advances in machine learning over the past decade have resulted in a proliferation of algorithmic applications for encoding, characterizing, and acting on complex data that may con…
TelescopeML -- I. An End-to-End Python Package for Interpreting Telescope Datasets through Training Machine Learning Models, Generating Statistical Reports, and Visualizing Results
Ehsan, Gharib-Nezhad, Natasha E. Batalha +4
We are on the verge of a revolutionary era in space exploration, thanks to advancements in telescopes such as the James Webb Space Telescope (\textit{JWST}). High-resolution, high…
ExoMiner: A Highly Accurate and Explainable Deep Learning Classifier that Validates 301 New Exoplanets
Hamed Valizadegan, Miguel Martinho, Laurent S. Wilkens +10
The kepler and TESS missions have generated over 100,000 potential transit signals that must be processed in order to create a catalog of planet candidates. During the last few yea…