Bayesian inference provides a consistent method for the extraction of information from
physics experiments even in ill-conditioned circumstances. The approach provides a unified …

In the past decade, substantial progress has been made in model-based optimization of
sampling designs for map**. This paper is an update of the overview of sampling designs …

The recent inference of sulfur dioxide (SO2) in the atmosphere of the hot (approximately
1,100 K), Saturn-mass exoplanet WASP-39b from near-infrared JWST observations …

emcee is a Python library implementing a class of affine-invariant ensemble samplers for
Markov chain Monte Carlo (MCMC). This package has been widely applied to probabilistic …

Bayesian inference has found widespread application and use in science and engineering
to reconcile Earth system models with data, including prediction in space (interpolation) …

The Advanced LIGO and Advanced Virgo gravitational-wave (GW) detectors will begin
operation in the coming years, with compact binary coalescence events a likely source for …

We present a newly developed Multivariate Copula Analysis Toolbox (MvCAT) which
includes a wide range of copula families with different levels of complexity. MvCAT employs …

Quantification of the global irrigation water use (IWU) is crucial to understanding the
anthropogenic disturbance of the natural hydrological cycle and optimal agricultural water …

Hot Jupiters are among the best-studied exoplanets, but it is still poorly understood how their
chemical composition and cloud properties vary with longitude. Theoretical models predict …

The pressing need to restart socioeconomic activities locked-down to control the spread of
SARS-CoV-2 in Italy must be coupled with effective methodologies to selectively relax …