Parameter estimation in differential equation models is a critical endeavour in the mathematical modelling of dynamic systems. Such models, represented by ordinary differential equations (ODEs), ...

Historically, data center design was linear: Size the facility to meet demand forecasts and hope for the best. Power and ...

The Navier–Stokes partial differential equation was developed in the early 19th century by Claude-Louis Navier and George ...

Artificial intelligence (AI) systems, particularly artificial neural networks, have proved to be highly promising tools for ...

Delay differential equations (DDEs) are widely used in ecology, physiology and many other areas of applied science. Although the form of the DDE model is usually proposed based on scientific ...

Stochastic differential equations have been shown useful in describing random continuous time processes. Biomedical experiments often imply repeated measurements on a series of experimental units and ...

Cancer is viewed as a multistep process whereby a normal cell is transformed into a cancer cell through the acquisition of mutations. We reduce the complexities of cancer progression to a simple set ...

In this paper we examine the capacity of arbitrage-free neural stochastic differential equation market models to produce realistic scenarios for the joint dynamics of multiple European options on a ...

Did you know meteorologists forecast the weather using a bunch of different physics and mathematical equations? They use these equations to create what's known as numerical weather models to predict ...