In many situations across computational science and engineering, multiple computational
models are available that describe a system of interest. These different models have varying …

A Hilbert space embedding of a distribution—in short, a kernel mean embedding—has
recently emerged as a powerful tool for machine learning and statistical inference. The basic …

Soils store more carbon than other terrestrial ecosystems,. How soil organic carbon (SOC)
forms and persists remains uncertain,, which makes it challenging to understand how it will …

We present, a general-purpose Bayesian analysis code aimed at models with complex
internal interdependencies. Without the need for specific code by the user …

We present a method to flexibly and self-consistently determine individual galaxies' star
formation rates (SFRs) from their host haloes' potential well depths, assembly histories, and …

MontePython is a parameter inference package for cosmology. We present the latest
development of the code over the past couple of years. We explain, in particular, two new …

At a distance of 1.295 parsecs, the red dwarf Proxima Centauri (α Centauri C, GL 551, HIP
70890 or simply Proxima) is the Sun's closest stellar neighbour and one of the best-studied …

Ultrahot giant exoplanets receive thousands of times Earth's insolation 1, 2. Their high-
temperature atmospheres (greater than 2,000 kelvin) are ideal laboratories for studying …

Mobile Edge Computing (MEC) is considered an essential future service for the
implementation of 5G networks and the Internet of Things, as it is the best method of …

Many problems in the physical sciences, machine learning, and statistical inference
necessitate sampling from a high-dimensional, multimodal probability distribution. Markov …