17 citations · 19 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…
ExoMiner++: Enhanced Transit Classification and a New Vetting Catalog for 2-Minute TESS Data
Hamed Valizadegan, Miguel J. S. Martinho, Jon M. Jenkins +24
We present ExoMiner++, an enhanced deep learning model that builds on the success of ExoMiner to improve transit signal classification in 2-minute TESS data. ExoMiner++ incorporate…
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…
Multiplicity Boost Of Transit Signal Classifiers: Validation of 69 New Exoplanets Using The Multiplicity Boost of ExoMiner
Hamed Valizadegan, Miguel J. S. Martinho, Jon M. Jenkins +3
Most existing exoplanets are discovered using validation techniques rather than being confirmed by complementary observations. These techniques generate a score that is typically t…