18 citations · 39 across the 16 of their papers we have counts for
16 papers
A Score-based Nonlinear Filter for Data Assimilation
Feng Bao, Zezhong Zhang, Guannan Zhang
We introduce a score-based generative sampling method for solving the nonlinear filtering problem with robust accuracy. A major drawback of existing nonlinear filtering methods, e.…
Parameter Estimation for the Truncated KdV Model through a Direct Filter Method
Hui Sun, Nick Moore, Feng Bao
In this work, we develop a computational method that to provide realtime detection for water bottom topography based on observations on surface measurements, and we design an inver…
Convergence Analysis for Training Stochastic Neural Networks via Stochastic Gradient Descent
Richard Archibald, Feng Bao, Yanzhao Cao +1
In this paper, we carry out numerical analysis to prove convergence of a novel sample-wise back-propagation method for training a class of stochastic neural networks (SNNs). The st…
A Stochastic Maximum Principle Approach for Reinforcement Learning with Parameterized Environment
Richard Archibald, Feng Bao, Jiongmin Yong
In this work, we introduce a stochastic maximum principle (SMP) approach for solving the reinforcement learning problem with the assumption that the unknowns in the environment can…
A PDE-based Adaptive Kernel Method for Solving Optimal Filtering Problems
Zezhong Zhang, Richard Archibald, Feng Bao
In this paper, we introduce an adaptive kernel method for solving the optimal filtering problem. The computational framework that we adopt is the Bayesian filter, in which we recur…
A Kernel Learning Method for Backward SDE Filter
Richard Archibald, Feng Bao
In this paper, we develop a kernel learning backward SDE filter method to estimate the state of a stochastic dynamical system based on its partial noisy observations. A system of f…
A Drift Homotopy Implicit Particle Filter Method for Nonlinear Filtering problems
Xin Li, Feng Bao, Kyle Gallivan
In this paper, we develop a drift homotopy implicit particle filter method. The methodology of our approach is to adopt the concept of drift homotopy in the resampling procedure of…
Meshfree Approximation for Stochastic Optimal Control Problems
Hui Sun, Feng Bao
In this work, we study the gradient projection method for solving a class of stochastic control problems by using a mesh free approximation approach to implement spatial dimension…
Solving Backward Doubly Stochastic Differential Equations through Splitting Schemes
Feng Bao, Yanzhao Cao, He Zhang
A splitting scheme for backward doubly stochastic differential equations is proposed. The main idea is to decompose a backward doubly stochastic differential equation into a backwa…
A Backward SDE Method for Uncertainty Quantification in Deep Learning
Richard Archibald, Feng Bao, Yanzhao Cao +1
We develop a probabilistic machine learning method, which formulates a class of stochastic neural networks by a stochastic optimal control problem. An efficient stochastic gradient…
An efficient numerical algorithm for solving data driven feedback control problems
Richard Archibald, Feng Bao, Jiongmin Yong +1
The goal of this paper is to solve a class of stochastic optimal control problems numerically, in which the state process is governed by an Itô type stochastic differential equatio…
Analytic Continuation of Noisy Data Using Adams Bashforth ResNet
Xuping Xie, Feng Bao, Thomas Maier +1
We propose a data-driven learning framework for the analytic continuation problem in numerical quantum many-body physics. Designing an accurate and efficient framework for the anal…
Backward SDE Filter for Jump Diffusion Processes and Its Applications in Material Sciences
Richard Archibald, Feng Bao, Peter Maksymovych
The connection between forward backward doubly stochastic differential equations and the optimal filtering problem is established without using the Zakai's equation. The solutions…
Fast and Efficient Stochastic Optimization for Analytic Continuation
F. Bao, Y. Tang, M. Summers +4
The analytic continuation of imaginary-time quantum Monte Carlo data to extract real-frequency spectra remains a key problem in connecting theory with experiment. Here we present a…
Forward Backward Doubly Stochastic Differential Equations and the Optimal Filtering of Diffusion Processes
Feng Bao, Yanzhao Cao, Xiaoping Han
The connection between forward backward doubly stochastic differential equations and the optimal filtering problem is established without using the Zakai's equation. The solutions…
An Efficient Meshfreee Implicit Filter for Nonlinear Filtering Problems
Feng Bao, Yanzhao Cao, Clayton Webster +1
In this paper, we propose a meshfree approximation method for the implicit filter developed in [2], which is a novel numerical algorithm for nonlinear filtering problems. The impli…