Abstract: Stochastic process models are a type of model that explicitly include elements of probability in describing an organization, facilitating different modes of analysis and simulation. Having ...

The development of humans and other animals unfolds gradually over time, with cells taking on specific roles and functions via a process called cell fate determination. The fate of individual cells, ...

Stochastic differential equations (SDEs) provide a foundational framework for modelling systems subject to randomness, incorporating both continuous fluctuations and abrupt changes. In recent decades ...

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Abstract: Deterministic Turing machines and their associated complexity measures, by construction, cannot capture the complexity of the output of stochastic processes - like those in the real world.

As global financial markets become increasingly interconnected, accurately modelling correlations between assets is essential. Traditional models often assume static correlations, which fail to ...

This project provides an interactive Streamlit application for simulating and visualizing two important stochastic processes: the Poisson process and the Merton Jump Diffusion Model. Users can explore ...

ABSTRACT: This paper concerns the compactness and separability properties of the normed Boolean algebras (N.B.A.) with respect to topology generated by a distance equal to the square root of a measure ...

ABSTRACT: The mathematical theory of ranked-choice voting is reviewed, with particular focus on Condorcet, Plurality, and Borda Count methods. Maximizing the Borda Count score is shown to be ...

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