Nonlinear dynamics provides an essential framework for exploring complex phenomena in biological and medical sciences. By ...

THE teaching of differential equations in English universities usually ... would form an excellent addendum to a course in curve tracing, the two together being used to illuminate wide tracts ...

An acausal modeling framework for automatically parallelized scientific machine learning (SciML) in Julia. A computer algebra system for integrated symbolics for physics-informed machine learning and ...

He advises students on careers in actuarial science, and was active in developing calculus reform materials and extending that approach into the sophomore year in the multivariable calculus and ...

The course gives an introduction to the most common numerical methods for stochastic differential equations. have a thorough understanding of stochastic methods that are in-between mathematical ...

The course provides a thorough introduction to design, analysis (both theoretical and empirical), and programming of difference and elemental methods to solve differential equations. In addition, the ...

We propose a novel machine learning architecture, termed model-integrated neural networks (MINN), that can learn the physics-based dynamics of general autonomous or non-autonomous systems consisting ...