Jian Wang

collaborators

4 papers

math.PR2025

Convergence rates for the $p$ -Wasserstein distance of the empirical measures of an ergodic Markov process

René L. Schilling, Jian Wang, Bingyao Wu +1

Let $X := (X_{t})_{t \geq 0}$ be an ergodic Markov process on $ℜ^{d}$ , and $p > 0$ . We derive upper bounds of the $p$ -Wasserstein distance between the invariant measure and the empirica…

math.PR2025

Ergodicity of conditional McKean-Vlasov jump diffusions

Jianhai Bao, Yao Liu, Jian Wang

In this paper, we are interested in conditional McKean-Vlasov jump diffusions, which are also termed as McKean-Vlasov stochastic differential equations with jump idiosyncratic nois…

math.PR2025

Stationary distributions of McKean-Vlasov SDEs with jumps: existence, uniqueness, and multiplicity

Jianhai Bao, Jian Wang

In this paper, we are interested in the issues on existence, uniqueness, and multiplicity of stationary distributions for McKean-Vlasov SDEs with jumps. In detail, with regarding t…

math.PR2024

Geometric ergodicity of modified Euler schemes for SDEs with super-linearity

Jianhai Bao, Mateusz B. Majka, Jian Wang

As a well-known fact, the classical Euler scheme works merely for SDEs with coefficients of linear growth. In this paper, we study a general framework of modified Euler schemes, wh…

Convergence rates for the p-Wasserstein distance of the empirical measures of an ergodic Markov process

Ergodicity of conditional McKean-Vlasov jump diffusions

Stationary distributions of McKean-Vlasov SDEs with jumps: existence, uniqueness, and multiplicity

Geometric ergodicity of modified Euler schemes for SDEs with super-linearity

Convergence rates for the $p$ -Wasserstein distance of the empirical measures of an ergodic Markov process