3 citations · 5 across the 9 of their papers we have counts for
9 papers
To What Extent Are Star Cluster Ages Encoded in Their Environments? Exploring the Spatial Distribution of Age-Related Information with PHANGS-HST Imaging and Convolutional Neural Networks
Javier Viaña, Janice C. Lee, Andrew Vanderburg +12
The environments around star clusters evolve as stellar feedback reshapes the interstellar medium and dynamical processes reorganize the structure of the surrounding stellar field.…
Identifying Exoplanets with Deep Learning VI. Enhancing neural network mitigation of stellar activity RV signals with additional metrics
Naomi McWilliam, Zoë L. de Beurs, Andrew Vanderburg +12
The measurement of exoplanet masses using the radial velocity (RV) technique is currently limited by stellar activity, which introduces quasiperiodic variability signals that must…
A Machine-Learning Compositional Study of Exoplanetary Material Accreted Onto Five Helium-Atmosphere White Dwarfs with
Mariona Badenas-Agusti, Siyi Xu, Andrew Vanderburg +8
We present the first application of the Machine Learning (ML) pipeline to determine the physical parameters and photospheric composition of five metal-polluted H…
LensNet: Enhancing Real-time Microlensing Event Discovery with Recurrent Neural Networks in the Korea Microlensing Telescope Network
Javier Viaña, Kyu-Ha Hwang, Zoë de Beurs +20
Traditional microlensing event vetting methods require highly trained human experts, and the process is both complex and time-consuming. This reliance on manual inspection often le…
Absence of a Correlation between White Dwarf Planetary Accretion and Primordial Stellar Metallicity
Sydney Jenkins, Andrew Vanderburg, Allyson Bieryla +8
Over a quarter of white dwarfs have photospheric metal pollution, which is evidence for recent accretion of exoplanetary material. While a wide range of mechanisms have been propos…
Front-propagation Algorithm: Explainable AI Technique for Extracting Linear Function Approximations from Neural Networks
Javier Viaña
This paper introduces the front-propagation algorithm, a novel eXplainable AI (XAI) technique designed to elucidate the decision-making logic of deep neural networks. Unlike other…
cecilia: A Machine Learning-Based Pipeline for Measuring Metal Abundances of Helium-rich Polluted White Dwarfs
M. Badenas-Agusti, J. Viaña, A. Vanderburg +4
Over the past several decades, conventional spectral analysis techniques of polluted white dwarfs have become powerful tools to learn about the geology and chemistry of extrasolar…
Detection and Preliminary Characterisation of Polluted White Dwarfs from Gaia EDR3 and LAMOST
Mariona Badenas-Agusti, Andrew Vanderburg, Simon Blouin +4
We present a catalogue of 62 polluted white dwarfs observed by the 9th Low-Resolution Data Release of the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST LRS DR9v…
Simulation-based Inference for Exoplanet Atmospheric Retrieval: Insights from winning the Ariel Data Challenge 2023 using Normalizing Flows
Mayeul Aubin, Carolina Cuesta-Lazaro, Ethan Tregidga +9
Advancements in space telescopes have opened new avenues for gathering vast amounts of data on exoplanet atmosphere spectra. However, accurately extracting chemical and physical pr…