DeepMind’s AI finds new, proven solutions to Navier-Stokes equations—advancing fluid dynamics and future climate, flight, and ...

Several fundamental results on the existence and behavior of solutions to semilinear functional differential equations are developed in a Banach space setting. The ideas are applied to ...

This course is available on the BSc in Mathematics and Economics, BSc in Mathematics with Data Science, BSc in Mathematics with Economics, BSc in Mathematics, Statistics and Business, Erasmus ...

Stochastic dynamical systems arise in many scientific fields, such as asset prices in financial markets, neural activity in ...

Abstract: Many problems in science and engineering can be mathematically modeled using partial differential equations (PDEs), which are essential for fields like computational fluid dynamics (CFD), ...

Abstract: Inhomogeneous linear ordinary differential equations (ODEs) and systems of ODEs can be solved in a variety of ways. However, hardware circuits that can perform the efficient analog ...

Neural networks inspired by differential equations have proliferated for the past several years. Neural ordinary differential equations (NODEs) and neural controlled differential equations (NCDEs) are ...

The coordinates of the turning point and the equation of the line of symmetry can be found by writing the quadratic expression in completed square form. Find the equation of the line of symmetry and ...

TensorFlow implementation for DAS-PINNs: A deep adaptive sampling method for solving high-dimensional partial differential equations. Physics-informed neural networks are a type of promising tools to ...

Please see the Module Guides section on the Course Structure and Content pages of the Department of Mathematics for details on this module.

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