Feng Bao

According to our database, Feng Bao authored at least 21 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Transferable Neural Networks for Partial Differential Equations.

Zezhong Zhang, Feng Bao, Lili Ju, Guannan Zhang

J. Sci. Comput., April, 2024

Numerical Analysis for Convergence of a Sample-Wise Backpropagation Method for Training Stochastic Neural Networks.

Richard Archibald, Feng Bao, Yanzhao Cao, Hui Sun

SIAM J. Numer. Anal., 2024

2023

A stochastic maximum principle approach for reinforcement learning with parameterized environment.

Richard Archibald, Feng Bao, Jiongmin Yong

J. Comput. Phys., September, 2023

Splitting scheme for backward doubly stochastic differential equations.

Feng Bao, Yanzhao Cao, He Zhang

Adv. Comput. Math., August, 2023

Improving the Expressive Power of Deep Neural Networks through Integral Activation Transform.

Zezhong Zhang, Feng Bao, Guannan Zhang

CoRR, 2023

Diffusion-Model-Assisted Supervised Learning of Generative Models for Density Estimation.

Yanfang Liu, Minglei Yang, Zezhong Zhang, Feng Bao, Yanzhao Cao, Guannan Zhang

CoRR, 2023

An Ensemble Score Filter for Tracking High-Dimensional Nonlinear Dynamical Systems.

Feng Bao, Zezhong Zhang, Guannan Zhang

CoRR, 2023

TransNet: Transferable Neural Networks for Partial Differential Equations.

Zezhong Zhang, Feng Bao, Lili Ju, Guannan Zhang

CoRR, 2023

Parameter Estimation for the Truncated KdV Model through a Direct Filter Method.

Hui Sun, Nick Moore, Feng Bao

CoRR, 2023

2022

Kernel learning backward SDE filter for data assimilation.

Richard Archibald, Feng Bao

J. Comput. Phys., 2022

Convergence Analysis for Training Stochastic Neural Networks via Stochastic Gradient Descent.

Richard Archibald, Feng Bao, Yanzhao Cao, Hui Sun

CoRR, 2022

A PDE-based Adaptive Kernel Method for Solving Optimal Filtering Problems.

Zezhong Zhang, Richard Archibald, Feng Bao

CoRR, 2022

A Kernel Learning Method for Backward SDE Filter.

Richard Archibald, Feng Bao

CoRR, 2022

2021

Meshfree Approximation for Stochastic Optimal Control Problems.

Hui Sun, Feng Bao

CoRR, 2021

Solving Backward Doubly Stochastic Differential Equations through Splitting Schemes.

Feng Bao, Yanzhao Cao, He Zhang

CoRR, 2021

2020

An Efficient Numerical Algorithm for Solving Data Driven Feedback Control Problems.

Richard Archibald, Feng Bao, Jiongmin Yong, Tao Zhou

J. Sci. Comput., 2020

Uncertainty Quantification in Deep Learning through Stochastic Maximum Principle.

Richard Archibald, Feng Bao, Yanzhao Cao, He Zhang

CoRR, 2020

2019

A direct filter method for parameter estimation.

Richard Archibald, Feng Bao, Xuemin Tu

J. Comput. Phys., 2019

2016

A First Order Scheme for Backward Doubly Stochastic Differential Equations.

Feng Bao, Yanzhao Cao, Amnon J. Meir, Weidong Zhao

SIAM/ASA J. Uncertain. Quantification, 2016

Hierarchical optimization for neutron scattering problems.

Feng Bao, Rick Archibald, Dipanshu Bansal, Olivier Delaire

J. Comput. Phys., 2016

2014

A Hybrid Sparse-Grid Approach for Nonlinear Filtering Problems Based on Adaptive-Domain of the Zakai Equation Approximations.

Feng Bao, Yanzhao Cao, Clayton G. Webster, Guannan Zhang

SIAM/ASA J. Uncertain. Quantification, 2014