Parallel tempering is a generic Markov chain Monte Carlo sampling method which allows good mixing with multimodal target distributions, where conventional Metropolis-Hastings algorithms often fail.

An efficient and reliable a posteriori error estimate is derived for linear parabolic equations which does not depend on any regularity assumption on the underlying ...

Adaptive algorithms have immensely advanced, becoming integral for innovation across multiple industries. These intelligent systems adjust content and strategies to improve the experiences of users by ...