96 citations · 512 across the 35 of their papers we have counts for
35 papers
Machine Learning and galaxy morphology: for what purpose?
Didier Fraix-Burnet
Classification of galaxies is traditionally associated with their morphologies through visual inspection of images. The amount of data to come renders this task inhuman and Machine…
Unsupervised classification of CIGALE galaxy spectra
J Dubois, D Fraix-Burnet, J Moultaka +2
Aims. The present study aims at providing a deeper insight into the power and limitation of an unsupervised classification algorithm (called Fisher-EM) on spectra of galaxies. This…
Unsupervised classification of SDSS galaxy spectra
Didier Fraix-Burnet, C. Bouveyron, J. Moultaka
Defining templates of galaxy spectra is useful to quickly characterise new observations and organise databases from surveys. These templates are usually built from a pre-defined cl…
A Maximum Parsimony analysis of the effect of the environment on the evolution of galaxies
Didier Fraix-Burnet, Mauro d'Onofrio, Paola Marziani
Context. Galaxy evolution and the effect of environment are most often studied using scaling relations or some regression analyses around some given property. These approaches howe…
A phylogenetic approach to chemical tagging. Reassembling open cluster stars
Sergi Blanco-Cuaresma, Didier Fraix-Burnet
Context. The chemical tagging technique is a promising approach to reconstruct the history of the Galaxy by only using stellar chemical abundances. Different studies have undertake…
Unsupervised Classification of Galaxies. I. ICA feature selection
Tanuka Chattopadhyay, Didier Fraix-Burnet, Saptarshi Mondal
Subjective classification of galaxies can mislead us in the quest of the origin regarding formation and evolution of galaxies since this is necessarily limited to a few features. T…