This tutorial paper reviews the use of advanced Monte Carlo sampling methods in the
context of Bayesian model updating for engineering applications. Markov Chain Monte …

Sampling-based inference techniques are central to modern cosmological data analysis;
these methods, however, scale poorly with dimensionality and typically require approximate …

We use Gaia data release 2 (DR2) magnitudes, colours, and parallaxes for stars with G< 12
to explore a parameter space with 15 dimensions that simultaneously includes the initial …

Heterogeneity in the size distribution of cancer cell populations is linked to drug resistance
and invasiveness. However, understanding how such heterogeneity arises is still damped …

The rate of adaptive evolution depends on the rate at which beneficial mutations are
introduced into a population and the fitness effects of those mutations. The rate of beneficial …

Modern astronomy has been rapidly increasing our ability to see deeper into the Universe,
acquiring enormous samples of cosmic populations. Gaining astrophysical insights from …

The Canada–France Imaging Survey: Reconstructing the Milky Way Star Formation History
from Its White Dwarf Population - IOPscience This site uses cookies. By continuing to use this …

Likelihood-free methods are often required for inference in systems biology. While
approximate Bayesian computation (ABC) provides a theoretical solution, its practical …

Gaussian processes offers a convenient way to perform nonparametric reconstructions of
observational data assuming only a kernel which describes the covariance between …

Context. This work is part of the Gaia Data Processing and Analysis Consortium papers
published with the Gaia Early Data Release 3 (EDR3). It is one of the demonstration papers …