activity
20142025
most citedProbabilistic Random Forest: A machine learning algorithm for noisy datasets

196 citations · 1.5k across the 25 of their papers we have counts for

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Showing 2019Show all

5 papers · 1 filter

astro-ph.HE2019★ 28 cited

Exploring the Diversity of Type 1 Active Galactic Nuclei Identified in SDSS-IV/SPIDERS

Julien Wolf, Mara Salvato, Damien Coffey +8

We present a statistical analysis of the optical properties of an X-ray selected Type 1 AGN sample, using high signal to-noise ratio () spectra of the counterparts of the R…

astro-ph.GA2019★ 102 cited

The multiphase gas structure and kinematics in the circumnuclear region of NGC 5728

T. Taro Shimizu, R. I. Davies, D. Lutz +22

We report on our combined analysis of HST, VLT/MUSE, VLT/SINFONI, and ALMA observations of the local Seyfert 2 galaxy, NGC 5728 to investigate in detail the feeding and feedback of…

astro-ph.IM2019★ 137 cited

Machine Learning in Astronomy: a practical overview

Dalya Baron

Astronomy is experiencing a rapid growth in data size and complexity. This change fosters the development of data-driven science as a useful companion to the common model-driven da…

astro-ph.GA2019★ 111 cited

Discovering AGN-driven winds through their infrared emission: II. Mass outflow rate and energetics

Dalya Baron, Hagai Netzer

The global influence of AGN-driven outflows remains uncertain, due to a lack of large samples with accurately-determined outflow properties. In the second paper of this series, we…

astro-ph.GA2019★ 56 cited

Black hole mass estimation for Active Galactic Nuclei from a new angle

Dalya Baron, Brice Ménard

The scaling relations between supermassive black holes and their host galaxy properties are of fundamental importance in the context black hole-host galaxy co-evolution throughout…