16 citations · 52 across the 15 of their papers we have counts for
4 papers · 1 filter
Hunting for "Oddballs" with Machine Learning: Detecting Anomalous Exoplanets Using a Deep-Learned Low-Dimensional Representation of Transit Spectra with Autoencoders
Alexander Roman, Emilie Panek, Roy T. Forestano +3
This study explores the application of autoencoder-based machine learning techniques for anomaly detection to identify exoplanet atmospheres with unconventional chemical signatures…
Supervised Machine Learning Methods with Uncertainty Quantification for Exoplanet Atmospheric Retrievals from Transmission Spectroscopy
Roy T. Forestano, Konstantin T. Matchev, Katia Matcheva +1
Standard Bayesian retrievals for exoplanet atmospheric parameters from transmission spectroscopy, while well understood and widely used, are generally computationally expensive. In…
Reproducing Bayesian Posterior Distributions for Exoplanet Atmospheric Parameter Retrievals with a Machine Learning Surrogate Model
Eyup B. Unlu, Roy T. Forestano, Konstantin T. Matchev +1
We describe a machine-learning-based surrogate model for reproducing the Bayesian posterior distributions for exoplanet atmospheric parameters derived from transmission spectra of…
Searching for Novel Chemistry in Exoplanetary Atmospheres using Machine Learning for Anomaly Detection
Roy T. Forestano, Konstantin T. Matchev, Katia Matcheva +1
The next generation of telescopes will yield a substantial increase in the availability of high-resolution spectroscopic data for thousands of exoplanets. The sheer volume of data…