A backward differential deep learning-based algorithm for solving high-dimensional nonlinear backward stochastic differential equations

arXiv:2404.08456v1 Announce Type: cross
Abstract: In this work, we propose a novel backward differential deep learning-based algorithm for solving high-dimensional nonlinear backward stochastic differential equations (BSDEs), where the deep neural network (DNN) models are trained not only on the inputs and labels but also the differentials of the corresponding labels. This is motivated by the fact that differential deep learning can provide an efficient approximation of the labels and their derivatives with respect to inputs. The BSDEs are reformulated as …

abstract algorithm arxiv cs.lg cs.na deep learning deep neural network differential dnn inputs labels math.na network neural network novel q-fin.cp stochastic type work