Abstract Backward Stochastic Differential Equations (BSDEs) have been widely employed in
various areas of social and natural sciences, such as the pricing and hedging of financial …

The proposed BSDE-based diffusion model represents a novel approach to diffusion
modeling, which extends the application of stochastic differential equations (SDEs) in …

Gene regulatory network can intuitively reflect the interaction between genes, and an in-
depth study of these relationships plays a significant role in the treatment and prevention of …

In this paper, we provide conditions which ensure that stochastic Lipschitz BSDEs admit
Malliavin differentiable solutions. We investigate the problem of existence of densities for the …

在构建基因调控网络的方法中ꎬ 贝叶斯网络模型可以直观地表达基因间的调控关系ꎬ
但在结构学习时的复杂度极高ꎬ 使得网络建模效率较低且规模有限. 因此ꎬ 本文提出一种基于父 …

Gene regulatory network provides an effective way to study functional genomes.
Reconstruction of gene regulatory network can better help us to reveal the regulatory …

We obtain upper and lower Gaussian-type bounds on the density of each component Y ti of
the solution Y t to a multidimensional non-Markovian backward SDE. Our approach is based …

In order to achieve reliable results via statistical methodology, one important goal is to
account for potential uncertainty. Shige Peng introduced an uncertainty counterpart of …

We consider linearizations of stochastic differential equations with additive noise using the
Karhunen-Lo\eve expansion. We obtain our linearizations by truncating the expansion and …