Abstract: Hyperspectral image (HSI) mixed noise removal is a fundamental problem and an important preprocessing step in remote sensing fields. The low-rank approximation-based methods have been ...

Abstract: As computing devices continue growing explosively, computational efficiency is increasingly important. To improve the efficiency of computations, approximate computing is widely used in ...

Approximation theory and asymptotic methods form a foundational framework that bridges classical ideas with modern numerical analysis, enabling researchers to obtain practical, near‐optimal solutions ...

Applied and Computational Mathematics and Statistics, University of Notre Dame, Notre Dame, IN, USA Characterizing the spiking statistics of neurons receiving noisy synaptic input is a central problem ...

Adequate mathematical modeling is the key to success for many real-world projects in engineering, medicine, and other applied areas. As soon as an appropriate mathematical model is developed, it can ...

A wealth of computationally efficient approximation methods for Gaussian process regression have been recently proposed. We give a unifying overview of sparse approximations, following ...

This course teaches commonly used approximation methods in quantum mechanics. They include time-independent perturbation theory, time-dependent perturbation theory, tight binding method, variational ...