Hence, researchers often simulate the brain as a network of coupled neural masses, each described by a mean-field model. These models capture the essential features of neuronal populations while ...

Multi-language suite for high-performance solvers of differential equations and scientific machine learning (SciML) components. Ordinary differential equations (ODEs), stochastic differential ...

Stochastic modelling is the development of mathematical models for non-deterministic physical systems, which can adopt many possible behaviours starting from any given initial condition. Monte ...

In a mesmerising blend of art and mathematics, a research student from University College London (UCL) has recently gained widespread attention for creating intricate images solely through ...

Abstract: This work develops and analyzes a class of adaptive biased stochastic optimization (ABSO) algorithms from the perspective of the GEneralized Adaptive gRadient (GEAR) method that contains ...

GANs are often criticized for being difficult to train, with their architectures relying heavily on empirical tricks. Despite their ability to generate high-quality images in a single forward pass, ...

Abstract: In this paper, we focus on a type of linear-quadratic (LQ) mean-field game of stochastic differential equation (SDE) with terminal state constraint and common noise, where a coupling ...

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 ...

The course gives a solid basic knowledge of stochastic processes, intended to be sufficient for applications on undergraduate and masters levels in engineering and natural sciences, as well as for ...

Develop your knowledge of numerical methods with an emphasis on numerical optimisation techniques, advanced methods for the numerical solution of ordinary differential equations and the application of ...

Develop your knowledge of numerical methods with an emphasis on numerical optimisation techniques, advanced methods for the numerical solution of ordinary differential equations and applying methods ...