3 papers
stat.ML2026
Scalable Bayesian Additive Models for Stellar Flare Detection via Amortized Gaussian Process Inference and Hidden Markov Models
Rodrigo Herrera, Vianey Leos-Barajas, Gwendolyn Eadie +2
Gaussian Processes (GPs) are a powerful tool for Bayesian time-series modeling, yet their cubic computational cost remains a severe barrier for application to long, high-cadence da…
stat.AP2026
Bayesian inference for hidden Markov models under genuine multimodality with application to ecological time series
Marco A. Gallegos-Herrada, Vianey Leos-Barajas, Jeffrey S. Rosenthal
Bayesian inference in hidden Markov models (HMMs) can be challenging due to the presence of multimodality in the likelihood function, and consequently in the joint posterior distri…
astro-ph.SR2024
Detecting stellar flares in photometric data using hidden Markov models
J. Arturo Esquivel, Yunyi Shen, Vianey Leos-Barajas +5
We present a hidden Markov model (HMM) for discovering stellar flares in light curve data of stars. HMMs provide a framework to model time series data that are not stationary; they…