We introduce higher-order Stein kernels relative to the standard Gaussian measure, which generalize usual by involving derivatives of test functions. relate associated discrepancies various metrics on space

The frozen Gaussian approximation provides a highly efficient computational method for high frequency wave propagation. The derivation of the method is based on asymptotic analysis. In this paper, for general linear strictly hyperbolic system, we establish the rigorous convergence result for frozen Gaussian approximation. As a byproduct, higher order frozen Gaussian approximation is developed.

The aim of this paper is to derive some consequences of the main result of Götze and Zaitsev [5] (see Theorem 2 below). We shall show that the i.i.d. case of this result implies the multidimensional version of a result of Sakhanenko [12]. We shall obtain bounds for the rate of strong Gaussian approximation of sums of i.i.d. R-valued random vectors ξj having finite moments E ‖ξj‖ , γ > 2. We con...

We consider the problem of computing a Gaussian approximation to posterior distribution parameter given N observations and prior. Owing need processing large sample sizes N, variety approximate tractable methods revolving around online learning have flourished over past decades. In present work, we propose use variational inference compute through single pass data. Our algorithm is recursive ve...