4 papers
Misspecification-robust amortised simulation-based inference using variational methods
Matthew O'Callaghan, Kaisey S. Mandel, Gerry Gilmore
Recent advances in neural density estimation have enabled powerful simulation-based inference (SBI) methods that can flexibly approximate Bayesian inference for intractable stochas…
Data-driven dust inference at mid-to-high Galactic latitudes using probabilistic machine learning
Matthew O'Callaghan, Kaisey S. Mandel, Gerry Gilmore
We present a method for accurately and precisely inferring photometric dust extinction towards stars at mid-to-high Galactic latitudes using probabilistic machine learning to model…
Quantifying Interstellar Extinction at High Galactic Latitudes
Matthew O'Callaghan, Gerry Gilmore, Kaisey S. Mandel
A detailed map of the distribution of dust at high Galactic latitudes is essential for future cosmic microwave background (CMB) polarization experiments because the dust, while dif…
Assembling a high-precision abundance catalogue of solar twins in GALAH for phylogenetic studies
Kurt Walsen, Paula Jofré, Sven Buder +13
Stellar chemical abundances have proved themselves a key source of information for understanding the evolution of the Milky Way, and the scale of major stellar surveys such as GALA…