70 citations · 79 across the 4 of their papers we have counts for
4 papers
A self-supervised, physics-aware, Bayesian neural network architecture for modelling galaxy emission-line kinematics
James M. Dawson, Timothy A. Davis, Edward L. Gomez +1
In the upcoming decades large facilities, such as the SKA, will provide resolved observations of the kinematics of millions of galaxies. In order to assist in the timely exploitati…
Lessons Learned from the 1st ARIEL Machine Learning Challenge: Correcting Transiting Exoplanet Light Curves for Stellar Spots
Nikolaos Nikolaou, Ingo P. Waldmann, Angelos Tsiaras +20
The last decade has witnessed a rapid growth of the field of exoplanet discovery and characterisation. However, several big challenges remain, many of which could be addressed usin…
Using machine learning to study the kinematics of cold gas in galaxies
James M. Dawson, Timothy A. Davis, Edward L. Gomez +3
Next generation interferometers, such as the Square Kilometre Array, are set to obtain vast quantities of information about the kinematics of cold gas in galaxies. Given the volume…
The MASSIVE survey - XI. What drives the molecular gas properties of early-type galaxies
Timothy A. Davis, Jenny E. Greene, Chung-Pei Ma +5
In this paper we study the molecular gas content of a representative sample of 67 of the most massive early-type galaxies in the local universe, drawn uniformly from the MASSIVE su…