Explores the convergence of Langevin Monte Carlo algorithms under different growth rates and smoothness conditions, emphasizing fast convergence for a wide class of potentials.
Explores error estimation in numerical methods for solving differential equations, focusing on local truncation error, stability, and Lipschitz continuity.
