Stochastic models have become indispensable tools for understanding growth dynamics in complex systems. By incorporating randomness and uncertainty into the modelling framework, these methods provide ...

Abstract: In this talk, we discuss the construction of admissible, physics-consistent and identifiable stochastic models for uncertainty quantification. We first consider a continuum mechanics setting ...

First of all, the problem scope and the theoretical foundation are presented. The considered ISC network is a layered network in which nodes represent points of interactions between the two layers.

Accurate forecasting of epidemic scenarios is critical to implementing effective public health intervention policies. Researchers used dynamical stochastic modeling techniques to reveal that infection ...

Characterizing the variability of the extragalactic sources used for calibration in the Atacama Large Millimeter/submillimeter Array (ALMA) is key to assess the flux scale uncertainty of science ...

ABSTRACT The problem of stochastic precipitation generation has long been of interest. A good generator should produce time series with statistical properties to match those of the real precipitation.

Stochastic volatility is the unpredictable nature of asset price volatility over time. It's a flexible alternative to the Black Scholes' constant volatility assumption.

The whole picture of Mathematical Modeling is systematically and thoroughly explained in this text for undergraduate and graduate students of mathematics, engineering, economics, finance, biology, ...