Explores explicit stabilised Runge-Kutta methods and their application to Bayesian inverse problems, covering optimization, sampling, and numerical experiments.
Covers numerical solutions to Schrödinger equations, quantum Monte Carlo simulations, tensor networks, quantum algorithms, and machine-learning approaches.
