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Transmission spectroscopy is one of the premier methods used to probe the temperature, composition, and cloud properties of exoplanet atmospheres. Recent studies have demonstrated that the multidimensional nature of exoplanet atmospheres --…

Earth and Planetary Astrophysics · Physics 2022-04-20 Ryan J. MacDonald , Nikole K. Lewis

Count-compositional data arise in many different fields, including high-throughput sequencing experiments, ecological surveys, and palaeoclimate studies, where a common, important goal is to understand how covariates relate to the observed…

Methodology · Statistics 2026-04-10 André F. B. Menezes , Andrew C. Parnell , Keefe Murphy

Ensemble learning is a statistical paradigm built on the premise that many weak learners can perform exceptionally well when deployed collectively. The BART method of Chipman et al. (2010) is a prominent example of Bayesian ensemble…

Machine Learning · Statistics 2018-10-08 Veronika Rockova , Enakshi Saha

To increase the sample size of future atmospheric characterization efforts, we build on the planetary infrared excess (PIE) technique that has been proposed as a means to detect and characterize the thermal spectra of transiting and…

Earth and Planetary Astrophysics · Physics 2021-11-03 Jacob Lustig-Yaeger , Kevin B. Stevenson , L. C. Mayorga , Kristin S. Sotzen , Erin M. May , Noam R. Izenberg , Kathleen Mandt

The most productive tracer of exoplanetary atmospheric escape is the measurement of excess absorption in the near-infrared metastable helium triplet during transits. Atmospheric escape of a close-in planet's atmosphere plays a role in its…

Earth and Planetary Astrophysics · Physics 2026-02-04 C. Farret Jentink , V. Bourrier , Y. Carteret

Bayesian Additive Regression Trees (BART) is a popular Bayesian non-parametric regression algorithm. The posterior is a distribution over sums of decision trees, and predictions are made by averaging approximate samples from the posterior.…

Machine Learning · Statistics 2022-10-19 Omer Ronen , Theo Saarinen , Yan Shuo Tan , James Duncan , Bin Yu

Most implementations of Bayesian additive regression trees (BART) one-hot encode categorical predictors, replacing each one with several binary indicators, one for every level or category. Regression trees built with these indicators…

Methodology · Statistics 2024-08-14 Sameer K. Deshpande

Bayesian Additive Regression Trees (BART) is a fully Bayesian approach to modeling with ensembles of trees. BART can uncover complex regression functions with high dimensional regressors in a fairly automatic way and provide Bayesian…

Machine Learning · Statistics 2018-07-11 Edward George , Prakash Laud , Brent Logan , Robert McCulloch , Rodney Sparapani

The ability for citizen scientists to analyze image data and search for exoplanets using images from small telescopes has the potential to greatly accelerate the search for exoplanets. Recent work on the Exoplanet Transit Interpretation…

Earth and Planetary Astrophysics · Physics 2020-06-25 Sujay Nair , Jonathan Varghese , Kalée Tock

Motivated by the remarkable success of Bayesian additive regression trees (BART) in regression modelling, we propose a novel nonparametric Bayesian method, termed Functional BART (FBART), tailored specifically for function-on-scalar…

Methodology · Statistics 2025-06-03 Jiahao Cao , Shiyuan He , Bohai Zhang

JWST observations are leading to important new insights into exoplanetary atmospheres through transmission spectroscopy. In order to harness the full potential of the broad spectral range and high sensitivity of JWST, atmospheric retrievals…

Earth and Planetary Astrophysics · Physics 2024-03-11 Savvas Constantinou , Nikku Madhusudhan

A new GEANT4 particle transport model -- the Atmospheric Radiation Interaction Simulator (AtRIS, Banjac et al. 2018a. J. Geophys. Res.) -- has been recently developed in order to model the interaction of radiation with planets. The upcoming…

Ensemble decision tree methods such as XGBoost, Random Forest, and Bayesian Additive Regression Trees (BART) have gained enormous popularity in data science for their superior performance in machine learning regression and classification…

Methodology · Statistics 2025-09-10 Shuren He , Huiyan Sang , Quan Zhou

The James Webb Space Telescope (JWST) will enable the search for and characterization of terrestrial exoplanet atmospheres in the habitable zone via transmission spectroscopy. However, relatively little work has been done to use solar…

Earth and Planetary Astrophysics · Physics 2023-08-30 Jacob Lustig-Yaeger , Victoria S. Meadows , David Crisp , Michael R. Line , Tyler D. Robinson

The effectiveness of Bayesian Additive Regression Trees (BART) has been demonstrated in a variety of contexts including non-parametric regression and classification. A BART scheme for estimating the intensity of inhomogeneous Poisson…

Statistics Theory · Mathematics 2022-11-15 Stamatina Lamprinakou , Mauricio Barahona , Seth Flaxman , Sarah Filippi , Axel Gandy , Emma McCoy

We present BART, a denoising autoencoder for pretraining sequence-to-sequence models. BART is trained by (1) corrupting text with an arbitrary noising function, and (2) learning a model to reconstruct the original text. It uses a standard…

Computation and Language · Computer Science 2019-10-31 Mike Lewis , Yinhan Liu , Naman Goyal , Marjan Ghazvininejad , Abdelrahman Mohamed , Omer Levy , Ves Stoyanov , Luke Zettlemoyer

We present EOS, a procedure for determining the Outgoing Longwave Radiation (OLR) and top-of-atmosphere (TOA) albedo for a wide range of conditions expected to be present in the atmospheres of rocky planets with temperate conditions. EOS is…

We present Exo-Transmit, a software package to calculate exoplanet transmission spectra for planets of varied composition. The code is designed to generate spectra of planets with a wide range of atmospheric composition, temperature,…

Earth and Planetary Astrophysics · Physics 2017-03-22 Eliza M. -R. Kempton , Roxana E. Lupu , Albert Owusu-Asare , Patrick Slough , Bryson Cale

Bayesian additive regression trees have seen increased interest in recent years due to their ability to combine machine learning techniques with principled uncertainty quantification. The Bayesian backfitting algorithm used to fit BART…

Machine Learning · Statistics 2022-02-22 Antonio R. Linero

Many time-to-event studies are complicated by the presence of competing risks. Such data are often analyzed using Cox models for the cause specific hazard function or Fine-Gray models for the subdistribution hazard. In practice regression…

Methodology · Statistics 2018-07-02 Rodney Sparapani , Brent R. Logan , Robert E. McCulloch , Purushottam W. Laud