Delves into uniformly accurate hydrodynamic models for kinetic equations using machine learning, covering Boltzmann equation, moment methods, and numerical results.
Explores explicit stabilised Runge-Kutta methods and their application to Bayesian inverse problems, covering optimization, sampling, and numerical experiments.
Covers numerical methods for solving differential equations and their stability analysis, focusing on error calculation and practical applications in engineering and science.
Covers numerical integration techniques, focusing on composite quadrature formulas and their applications for approximating integrals with improved accuracy.
