3 papers
astro-ph.CO2025
Markov Walk Exploration of Model Spaces: Bayesian Selection of Dark Energy Models with Supernovae
Benedikt Schosser, Tobias Röspel, Bjoern Malte Schaefer
Central to model selection is a trade-off between performing a good fit and low model complexity: A model of higher complexity should only be favoured over a simpler model if it pr…
astro-ph.CO2025
Approximating non-Gaussian Bayesian partitions with normalising flows: statistics, inference and application to cosmology
Tobias Röspel, Adrian Schlosser, Björn Malte Schäfer
Subject of this paper is the simplification of Markov chain Monte Carlo sampling as used in Bayesian statistical inference by means of normalising flows, a machine learning method…
cond-mat.stat-mech2025
Partition function approach to non-Gaussian likelihoods: information theory and state variables for Bayesian inference
Rebecca Maria Kuntz, Heinrich von Campe, Tobias Röspel +2
The significance of statistical physics concepts such as entropy extends far beyond classical thermodynamics. We interpret the similarity between partitions in statistical mechanic…