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

1 Introduction: Consequences of Numerical Inaccuracy 1 -- 1.1 Importance of Understanding Computational Statistics 1 -- 1.2 Brief History: Duhem to the Twenty-First Century 3 -- 1.3 Motivating Example ...

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 ...

Geochemical data are expressed in closed numerical systems due to their non-normality and the presence of outliers. The specificity of such data makes it challenging to analyze them using standard ...