45 citations · 111 across the 5 of their papers we have counts for
5 papers
Covariate Dependent Mixture of Bayesian Networks
Roman Marchant, Dario Draca, Gilad Francis +4
Learning the structure of Bayesian networks from data provides insights into underlying processes and the causal relationships that generate the data, but its usefulness depends on…
The MAGPI Survey: the evolution and drivers of gas turbulence in intermediate-redshift galaxies
Yifan Mai, Scott M. Croom, Emily Wisnioski +21
We measure the ionised gas velocity dispersions of star-forming galaxies in the MAGPI survey () and compare them with galaxies in the SAMI () and KROSS ($z\sim…
The SAMI Galaxy Survey: the difference between ionised gas and stellar velocity dispersions
Sree Oh, Matthew Colless, Francesco D'Eugenio +16
We investigate the mean locally-measured velocity dispersions of ionised gas () and stars () for 1090 galaxies with stellar masses $\log\,(M_*/M_{\odot}) \geq 9.5…
The SAMI Galaxy Survey: a statistical approach to an optimal classification of stellar kinematics in galaxy surveys
Jesse van de Sande, Sam P. Vaughan, Luca Cortese +22
Large galaxy samples from multi-object IFS surveys now allow for a statistical analysis of the z~0 galaxy population using resolved kinematics. However, the improvement in number s…
The SAMI Galaxy Survey: Gas velocity dispersions in low- star-forming galaxies and the drivers of turbulence
Mathew R. Varidel, Scott M. Croom, Geraint F. Lewis +18
We infer the intrinsic ionised gas kinematics for 383 star-forming galaxies across a range of integrated star-formation rates (SFR M yr) at $z…