Dynamical systems modeling, particularly via systems of ordinary differential equations, has
been used to effectively capture the temporal behavior of different biochemical components …

Bayesian inference is a popular approach towards parameter identification in engineering
problems. Such technique would involve iterative sampling methods which are often robust …

Probabilistic (Bayesian) modeling has experienced a surge of applications in almost all
quantitative sciences and industrial areas. This development is driven by a combination of …

We identify the phase of a cycle as a new critical factor for tipping points (critical transitions)
in cyclic systems subject to time-varying external conditions. As an example, we consider …

Spatially representative estimates of surface energy exchange from field measurements are
required for improving and validating Earth system models and satellite remote sensing …

Nonlinear time delay systems produce inherently delay-induced periodic oscillations, which
are, however, too idealistic compared to observations. We exhibit a unified stochastic …

Interactions between clouds, aerosol, and precipitation are crucial aspects of weather and
climate. The simple Koren–Feingold conceptual model is important for providing deeper …

The ocean mixed layer model (OMLM) is improved using the large-eddy simulation (LES)
and the inverse estimation method. A comparison of OMLM (Noh model) and LES results …

We approach the problem of convection and clouds using a “top‐down view” that focuses on
system‐wide behavior and emergent phenomena. We distinguish this from the traditional …

We identify the phase of a cycle as a new critical factor for tipping points (critical transitions)
in cyclic systems subject to time-varying external conditions. As an example, we consider …