Across modern data-intensive disciplines, the union of numerical computation, statistics, and machine learning has become ...

Large sparse linear systems arise in diverse fields such as structural engineering, fluid dynamics, network analysis and machine learning. Direct factorisation techniques often become impractical for ...

Neural networks suffer from spectral bias and have difficulty representing the high-frequency components of a function, whereas relaxation methods can resolve high frequencies efficiently but stall at ...

Design of Experiments (DOE) is a powerful and pragmatic tool for optimisation but it’s not the only way. Could there be even more powerful alternatives in the age of machine learning, AI and ...