Advances in machine learning methods provide tools that have broad applicability in
scientific research. These techniques are being applied across the diversity of nuclear …

Cardiac electrophysiology models are among the most mature and well‐studied
mathematical models of biological systems. This maturity is bringing new challenges as …

Heavy atomic nuclei have an excess of neutrons over protons, which leads to the formation
of a neutron skin whose thickness is sensitive to details of the nuclear force. This links …

To fully take advantage of the data provided by large-scale structure surveys, we need to
quantify the potential impact of baryonic effects, such as feedback from active galactic nuclei …

Subjecting a physical system to extreme conditions is one of the means often used to obtain
a better understanding and deeper insight into its organization and structure. In the case of …

Simulating the time evolution of Partial Differential Equations (PDEs) of large-scale systems
is crucial in many scientific and engineering domains such as fluid dynamics, weather …

Advances in scientific computing have allowed the development of complex models that are
being routinely applied to problems in disease epidemiology, public health and decision …

Abstract Model calibration is crucial for optimizing the performance of complex computer
models across various disciplines. In the era of Industry 4.0, symbolizing rapid technological …

Many computer models possess high-dimensional input spaces and substantial
computational time to produce a single model evaluation. Although such models are often …

In this paper we present a framework for addressing a variety of engineering design
challenges with limited empirical data and partial information. This framework includes …