A Hybrid Sparse-Grid Approach for Nonlinear Filtering Problems Based on Adaptive-Domain of the Zakai Equation Approximations. - Feng Bao 005; Yanzhao Cao; Clayton G. Webster; Guannan Zhang (SIAM/ASA J. Uncertain. Quantification, 2014)

Hierarchical optimization for neutron scattering problems. - Feng Bao 005; Rick Archibald; Dipanshu Bansal; Olivier Delaire (J. Comput. Phys., 2016)

A First Order Scheme for Backward Doubly Stochastic Differential Equations. - Feng Bao 005; Yanzhao Cao; Amnon J. Meir; Weidong Zhao (SIAM/ASA J. Uncertain. Quantification, 2016)

A direct filter method for parameter estimation. - Richard Archibald; Feng Bao 005; Xuemin Tu (J. Comput. Phys., 2019)

Uncertainty Quantification in Deep Learning through Stochastic Maximum Principle. - Richard Archibald; Feng Bao 005; Yanzhao Cao; He Zhang (CoRR, 2020)

An Efficient Numerical Algorithm for Solving Data Driven Feedback Control Problems. - Richard Archibald; Feng Bao 005; Jiongmin Yong; Tao Zhou (J. Sci. Comput., 2020)

Solving Backward Doubly Stochastic Differential Equations through Splitting Schemes. - Feng Bao 005; Yanzhao Cao; He Zhang (CoRR, 2021)

Meshfree Approximation for Stochastic Optimal Control Problems. - Hui Sun; Feng Bao 005 (CoRR, 2021)

A Kernel Learning Method for Backward SDE Filter. - Richard Archibald; Feng Bao 005 (CoRR, 2022)

A PDE-based Adaptive Kernel Method for Solving Optimal Filtering Problems. - Zezhong Zhang; Richard Archibald; Feng Bao 005 (CoRR, 2022)

Convergence Analysis for Training Stochastic Neural Networks via Stochastic Gradient Descent. - Richard Archibald; Feng Bao 005; Yanzhao Cao; Hui Sun (CoRR, 2022)

Kernel learning backward SDE filter for data assimilation. - Richard Archibald; Feng Bao 005 (J. Comput. Phys., 2022)

Parameter Estimation for the Truncated KdV Model through a Direct Filter Method. - Hui Sun; Nick Moore; Feng Bao 005 (CoRR, 2023)

TransNet: Transferable Neural Networks for Partial Differential Equations. - Zezhong Zhang; Feng Bao 005; Lili Ju; Guannan Zhang (CoRR, 2023)

An Ensemble Score Filter for Tracking High-Dimensional Nonlinear Dynamical Systems. - Feng Bao 005; Zezhong Zhang; Guannan Zhang (CoRR, 2023)

Diffusion-Model-Assisted Supervised Learning of Generative Models for Density Estimation. - Yanfang Liu; Minglei Yang 005; Zezhong Zhang; Feng Bao 005; Yanzhao Cao; Guannan Zhang (CoRR, 2023)

Improving the Expressive Power of Deep Neural Networks through Integral Activation Transform. - Zezhong Zhang; Feng Bao 005; Guannan Zhang (CoRR, 2023)

Splitting scheme for backward doubly stochastic differential equations. - Feng Bao 005; Yanzhao Cao; He Zhang (Adv. Comput. Math., 2023)

A stochastic maximum principle approach for reinforcement learning with parameterized environment. - Richard Archibald; Feng Bao 005; Jiongmin Yong (J. Comput. Phys., 2023)

A Scalable Training-Free Diffusion Model for Uncertainty Quantification. - Ali Haisam Muhammad Rafid; Junqi Yin; Yuwei Geng; Siming Liang; Feng Bao 005; Lili Ju; Guannan Zhang (SC Workshops, 2024)

A Scalable Real-Time Data Assimilation Framework for Predicting Turbulent Atmosphere Dynamics. - Junqi Yin; Siming Liang; Siyan Liu; Feng Bao 005; Hristo G. Chipilski; Dan Lu 001; Guannan Zhang (SC Workshops, 2024)

Convergence Analysis for A Stochastic Maximum Principle Based Data Driven Feedback Control Algorithm. - Siming Liang; Hui Sun; Richard Archibald; Feng Bao 005 (CoRR, 2024)

A score-based filter for nonlinear data assimilation. - Feng Bao 005; Zezhong Zhang; Guannan Zhang (J. Comput. Phys., 2024)

Numerical Analysis for Convergence of a Sample-Wise Backpropagation Method for Training Stochastic Neural Networks. - Richard Archibald; Feng Bao 005; Yanzhao Cao; Hui Sun (SIAM J. Numer. Anal., 2024)

Transferable Neural Networks for Partial Differential Equations. - Zezhong Zhang; Feng Bao 005; Lili Ju; Guannan Zhang (J. Sci. Comput., 2024)

Joint state-parameter estimation for the reduced fracture model via the united filter. - Phuoc-Toan Huynh; Thi-Thao-Phuong Hoang; Guannan Zhang; Feng Bao 005 (J. Comput. Phys., 2025)

Ensemble score filter with image inpainting for data assimilation in tracking surface quasi-geostrophic dynamics with partial observations. - Siming Liang; Hoang Tran; Feng Bao 005; Hristo G. Chipilski; Peter Jan van Leeuwen; Guannan Zhang (CoRR, 2025)

Numerical approximations for partially observed optimal control of stochastic partial differential equations. - Feng Bao 005; Yanzhao Cao; Hongjiang Qian (CoRR, 2025)

Diffusion-based supervised learning of generative models for efficient sampling of multimodal distributions. - Hoang Tran; Zezhong Zhang; Feng Bao 005; Dan Lu 001; Guannan Zhang (CoRR, 2025)

Federated Learning on Stochastic Neural Networks. - Jingqiao Tang; Ryan Bausback; Feng Bao 005; Richard Archibald (CoRR, 2025)

Stochastic Operator Network: A Stochastic Maximum Principle Based Approach to Operator Learning. - Ryan Bausback; Jingqiao Tang; Lu Lu; Feng Bao 005; Toan Huynh (CoRR, 2025)