13 citations · 41 across the 10 of their papers we have counts for
4 papers · 1 filter
STAR NRE: Solving supernova selection effects with set-based truncated auto-regressive neural ratio estimation
Konstantin Karchev, Roberto Trotta
Accounting for selection effects in supernova type Ia (SN Ia) cosmology is crucial for unbiased cosmological parameter inference -- even more so for the next generation of large, m…
Dark Matter Halo Parameters from Overheated Exoplanets via Bayesian Hierarchical Inference
María Benito, Konstantin Karchev, Rebecca K. Leane +3
Dark Matter (DM) can become captured, deposit annihilation energy, and hence increase the heat flow in exoplanets and brown dwarfs. Detecting such a DM-induced heating in a populat…
Bayesian evidence estimation from posterior samples with normalizing flows
Rahul Srinivasan, Marco Crisostomi, Roberto Trotta +2
We propose a novel method (), based on normalizing flows, to estimate the Bayesian evidence (and its numerical uncertainty) from a pre-existing set of samples drawn from the…
SIDE-real: Supernova Ia Dust Extinction with truncated marginal neural ratio estimation applied to real data
Konstantin Karchev, Matthew Grayling, Benjamin M. Boyd +3
We present the first fully simulation-based hierarchical analysis of the light curves of a population of low-redshift type Ia supernovae (SNae Ia). Our hardware-accelerated forward…