Feng Bao

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 21

Top Topics

Nonlinear Dynamical Systems

Parameter Estimation

Data Assimilation

Top Venues

J. Comput. Phys.

J. Sci. Comput.

SIAM J. Numer. Anal.

Publications

Siming Liang, Hui Sun, Richard Archibald, Feng Bao
Convergence Analysis for A Stochastic Maximum Principle Based Data Driven Feedback Control Algorithm. CoRR (2024)
Zezhong Zhang, Feng Bao, Lili Ju, Guannan Zhang
Transferable Neural Networks for Partial Differential Equations. J. Sci. Comput. 99 (1) (2024)
Feng Bao, Zezhong Zhang, Guannan Zhang
A score-based filter for nonlinear data assimilation. J. Comput. Phys. 514 (2024)
Junqi Yin, Siming Liang, Siyan Liu, Feng Bao, Hristo G. Chipilski, Dan Lu, Guannan Zhang
A Scalable Real-Time Data Assimilation Framework for Predicting Turbulent Atmosphere Dynamics. CoRR (2024)
Richard Archibald, Feng Bao, Yanzhao Cao, Hui Sun
Numerical Analysis for Convergence of a Sample-Wise Backpropagation Method for Training Stochastic Neural Networks. SIAM J. Numer. Anal. 62 (2) (2024)
Zezhong Zhang, Feng Bao, Guannan Zhang
Improving the Expressive Power of Deep Neural Networks through Integral Activation Transform. CoRR (2023)
Yanfang Liu, Minglei Yang, Zezhong Zhang, Feng Bao, Yanzhao Cao, Guannan Zhang
Diffusion-Model-Assisted Supervised Learning of Generative Models for Density Estimation. CoRR (2023)
Zezhong Zhang, Feng Bao, Lili Ju, Guannan Zhang
TransNet: Transferable Neural Networks for Partial Differential Equations. CoRR (2023)
Richard Archibald, Feng Bao, Jiongmin Yong
A stochastic maximum principle approach for reinforcement learning with parameterized environment. J. Comput. Phys. 488 (2023)
Feng Bao, Zezhong Zhang, Guannan Zhang
An Ensemble Score Filter for Tracking High-Dimensional Nonlinear Dynamical Systems. CoRR (2023)
Feng Bao, Yanzhao Cao, He Zhang
Splitting scheme for backward doubly stochastic differential equations. Adv. Comput. Math. 49 (4) (2023)
Hui Sun, Nick Moore, Feng Bao
Parameter Estimation for the Truncated KdV Model through a Direct Filter Method. CoRR (2023)
Richard Archibald, Feng Bao
Kernel learning backward SDE filter for data assimilation. J. Comput. Phys. 455 (2022)
Richard Archibald, Feng Bao, Yanzhao Cao, Hui Sun
Convergence Analysis for Training Stochastic Neural Networks via Stochastic Gradient Descent. CoRR (2022)
Zezhong Zhang, Richard Archibald, Feng Bao
A PDE-based Adaptive Kernel Method for Solving Optimal Filtering Problems. CoRR (2022)
Richard Archibald, Feng Bao
A Kernel Learning Method for Backward SDE Filter. CoRR (2022)
Feng Bao, Yanzhao Cao, He Zhang
Solving Backward Doubly Stochastic Differential Equations through Splitting Schemes. CoRR (2021)
Richard Archibald, Feng Bao, Yanzhao Cao, He Zhang
Uncertainty Quantification in Deep Learning through Stochastic Maximum Principle. CoRR (2020)
Richard Archibald, Feng Bao, Jiongmin Yong, Tao Zhou
An Efficient Numerical Algorithm for Solving Data Driven Feedback Control Problems. J. Sci. Comput. 85 (2) (2020)
Richard Archibald, Feng Bao, Xuemin Tu
A direct filter method for parameter estimation. J. Comput. Phys. 398 (2019)
Feng Bao, Rick Archibald, Dipanshu Bansal, Olivier Delaire
Hierarchical optimization for neutron scattering problems. J. Comput. Phys. 315 (2016)