39 citations · 71 across the 3 of their papers we have counts for
7 papers · 1 filter
3D extinction mapping of the Milky Way using Convolutional Neural Networks: Presentation of the method and demonstration in the Carina Arm region
D. Cornu, J. Montillaud, D. J. Marshall +2
Context. Several methods have been proposed to build 3D extinction maps of the Milky Way (MW), most often based on Bayesian approaches. Although some studies employed machine learn…
Deciphering the evolution of the Milky Way discs: Gaia APOGEE Kepler giant stars and the Besançon Galaxy Model
N. Lagarde, C. Reylé, C. Chiappini +13
We investigate the properties of the double sequences of the Milky Way discs visible in the [/Fe] vs [Fe/H] diagram. In the framework of Galactic formation and evolution, we dis…
A neural network-based methodology to select young stellar object candidates from IR surveys
David Cornu, Julien Montillaud
Observed Young Stellar Objects (YSOs) are used to study star formation and characterize star forming regions. For this purpose, YSO candidate catalogs are compiled from various sur…
Modeling the 3D Milky Way using Machine Learning with Gaia and infrared surveys
David Cornu
The observation of our home galaxy, the Milky Way (MW), is made difficult by our internal viewpoint. The Gaia survey that contains around 1.6 billion star distances is the new flag…
Multi-scale analysis of the Monoceros OB 1 star-forming region: II. Colliding filaments in the Monoceros OB1 molecular cloud
Julien Montillaud, Mika Juvela, Charlotte Vastel +24
We started a multi-scale analysis of G202.3+2.5, an intertwined filamentary region of Monoceros OB1. In Paper I, we examined the distributions of dense cores and protostars and fou…
Multi-scale analysis of the Monoceros OB 1 star-forming region: I. The dense core population
Julien Montillaud, Mika Juvela, Charlotte Vastel +24
Current theories and models attempt to explain star formation globally, from core scales to giant molecular cloud scales. A multi-scale observational characterisation of an entire…