5 papers
Diffusion-Based Stochastic Operator Networks for Uncertainty Quantification in Stochastic Partial Differential Equations
Phuoc-Toan Huynh, Richard Archibald, Feng Bao
We introduce a novel framework for uncertainty quantification of solution operators associated with stochastic partial differential equations (SPDEs). Although SPDEs play a central…
The Ensemble Schr{ö}dinger Bridge filter for Nonlinear Data Assimilation
Hui Sun
This work introduces a novel nonlinear optimal filtering method, termed the Ensemble Schr{ö}dinger Bridge nonlinear filter. The proposed filter combines the standard prediction ste…
Batch Sample-wise Stochastic Optimal Control via Stochastic Maximum Principle
Hui Sun, Feng Bao
In this work, we study the stochastic optimal control problem (SOC) mainly from the probabilistic view point, i.e. via the Stochastic Maximum principle (SMP) \cite{Peng4}. We adopt…
Convergence Analysis for A Stochastic Maximum Principle Based Data Driven Feedback Control Algorithm
Siming Liang, Hui Sun, Richard Archibald +1
This paper presents convergence analysis of a novel data-driven feedback control algorithm designed for generating online controls based on partial noisy observational data. The al…
Solving high dimensional FBSDE with deep signature techniques with application to nonlinear options pricing
Hui Sun, Feng Bao
We report two methods for solving FBSDEs of path dependent types of high dimensions. Specifically, we propose a deep learning framework for solving such problems using path signatu…