Feng Bao - RankMe

37 papers Journal 35Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Score Filter Enhanced Data Assimilation Framework for Data-Driven Dynamical Systems. CoRR Jingqiao Tang, Ryan Bausback, Feng Bao, Guannan Zhang, Phuoc-Toan Huynh
2026	J	`jnl`	A score-based diffusion model approach for adaptive learning of stochastic partial differential equation solutions. J. Comput. Phys. Phuoc-Toan Huynh, Ruth Lopez Fajardo, Guannan Zhang, Lili Ju, Feng Bao
2026	J	`jnl`	Error estimates of a training-free diffusion model for high-dimensional sampling. CoRR Pengjun Wang, Zezhong Zhang, Minglei Yang, Feng Bao, Yanzhao Cao, Guannan Zhang
2025	J	`jnl`	A Score-based Diffusion Model Approach for Adaptive Learning of Stochastic Partial Differential Equation Solutions. CoRR Toan Huynh, Ruth Lopez Fajardo, Guannan Zhang, Lili Ju, Feng Bao
2025	J	`jnl`	Diffusion-based supervised learning of generative models for efficient sampling of multimodal distributions. CoRR Hoang Tran, Zezhong Zhang, Feng Bao, Dan Lu, Guannan Zhang
2025	J	`jnl`	Ensemble score filter with image inpainting for data assimilation in tracking surface quasi-geostrophic dynamics with partial observations. CoRR Siming Liang, Hoang Tran, Feng Bao, Hristo G. Chipilski, Peter Jan van Leeuwen, Guannan Zhang
2025	J	`jnl`	Federated Learning on Stochastic Neural Networks. CoRR Jingqiao Tang, Ryan Bausback, Feng Bao, Richard Archibald
2025	J	`jnl`	Joint state-parameter estimation for the reduced fracture model via the united filter. J. Comput. Phys. Phuoc-Toan Huynh, Thi-Thao-Phuong Hoang, Guannan Zhang, Feng Bao
2025	J	`jnl`	Numerical approximations for partially observed optimal control of stochastic partial differential equations. CoRR Feng Bao, Yanzhao Cao, Hongjiang Qian
2025	J	`jnl`	Stochastic Operator Network: A Stochastic Maximum Principle Based Approach to Operator Learning. CoRR Ryan Bausback, Jingqiao Tang, Lu Lu, Feng Bao, Toan Huynh
2025	J	`jnl`	The Ensemble Schr{ö}dinger Bridge filter for Nonlinear Data Assimilation. CoRR Feng Bao, Hui Sun
2024	—	`conf`	A Scalable Real-Time Data Assimilation Framework for Predicting Turbulent Atmosphere Dynamics. SC Workshops Junqi Yin, Siming Liang, Siyan Liu, Feng Bao, Hristo G. Chipilski, Dan Lu, Guannan Zhang
2024	J	`jnl`	A Scalable Real-Time Data Assimilation Framework for Predicting Turbulent Atmosphere Dynamics. CoRR Junqi Yin, Siming Liang, Siyan Liu, Feng Bao, Hristo G. Chipilski, Dan Lu, Guannan Zhang
2024	—	`conf`	A Scalable Training-Free Diffusion Model for Uncertainty Quantification. SC Workshops Ali Haisam Muhammad Rafid, Junqi Yin, Yuwei Geng, Siming Liang, Feng Bao, Lili Ju, Guannan Zhang
2024	J	`jnl`	A score-based filter for nonlinear data assimilation. J. Comput. Phys. Feng Bao, Zezhong Zhang, Guannan Zhang
2024	J	`jnl`	Convergence Analysis for A Stochastic Maximum Principle Based Data Driven Feedback Control Algorithm. CoRR Siming Liang, Hui Sun, Richard Archibald, Feng Bao
2024	J	`jnl`	Numerical Analysis for Convergence of a Sample-Wise Backpropagation Method for Training Stochastic Neural Networks. SIAM J. Numer. Anal. Richard Archibald, Feng Bao, Yanzhao Cao, Hui Sun
2024	J	`jnl`	Transferable Neural Networks for Partial Differential Equations. J. Sci. Comput. Zezhong Zhang, Feng Bao, Lili Ju, Guannan Zhang
2023	J	`jnl`	A stochastic maximum principle approach for reinforcement learning with parameterized environment. J. Comput. Phys. Richard Archibald, Feng Bao, Jiongmin Yong
2023	J	`jnl`	An Ensemble Score Filter for Tracking High-Dimensional Nonlinear Dynamical Systems. CoRR Feng Bao, Zezhong Zhang, Guannan Zhang
2023	J	`jnl`	Diffusion-Model-Assisted Supervised Learning of Generative Models for Density Estimation. CoRR Yanfang Liu, Minglei Yang, Zezhong Zhang, Feng Bao, Yanzhao Cao, Guannan Zhang
2023	J	`jnl`	Improving the Expressive Power of Deep Neural Networks through Integral Activation Transform. CoRR Zezhong Zhang, Feng Bao, Guannan Zhang
2023	J	`jnl`	Parameter Estimation for the Truncated KdV Model through a Direct Filter Method. CoRR Hui Sun, Nick Moore, Feng Bao
2023	J	`jnl`	Splitting scheme for backward doubly stochastic differential equations. Adv. Comput. Math. Feng Bao, Yanzhao Cao, He Zhang
2023	J	`jnl`	TransNet: Transferable Neural Networks for Partial Differential Equations. CoRR Zezhong Zhang, Feng Bao, Lili Ju, Guannan Zhang
2022	J	`jnl`	A Kernel Learning Method for Backward SDE Filter. CoRR Richard Archibald, Feng Bao
2022	J	`jnl`	A PDE-based Adaptive Kernel Method for Solving Optimal Filtering Problems. CoRR Zezhong Zhang, Richard Archibald, Feng Bao
2022	J	`jnl`	Convergence Analysis for Training Stochastic Neural Networks via Stochastic Gradient Descent. CoRR Richard Archibald, Feng Bao, Yanzhao Cao, Hui Sun
2022	J	`jnl`	Kernel learning backward SDE filter for data assimilation. J. Comput. Phys. Richard Archibald, Feng Bao
2021	J	`jnl`	Meshfree Approximation for Stochastic Optimal Control Problems. CoRR Hui Sun, Feng Bao
2021	J	`jnl`	Solving Backward Doubly Stochastic Differential Equations through Splitting Schemes. CoRR Feng Bao, Yanzhao Cao, He Zhang
2020	J	`jnl`	An Efficient Numerical Algorithm for Solving Data Driven Feedback Control Problems. J. Sci. Comput. Richard Archibald, Feng Bao, Jiongmin Yong, Tao Zhou
2020	J	`jnl`	Uncertainty Quantification in Deep Learning through Stochastic Maximum Principle. CoRR Richard Archibald, Feng Bao, Yanzhao Cao, He Zhang
2019	J	`jnl`	A direct filter method for parameter estimation. J. Comput. Phys. Richard Archibald, Feng Bao, Xuemin Tu
2016	J	`jnl`	A First Order Scheme for Backward Doubly Stochastic Differential Equations. SIAM/ASA J. Uncertain. Quantification Feng Bao, Yanzhao Cao, Amnon J. Meir, Weidong Zhao
2016	J	`jnl`	Hierarchical optimization for neutron scattering problems. J. Comput. Phys. Feng Bao, Rick Archibald, Dipanshu Bansal, Olivier Delaire
2014	J	`jnl`	A Hybrid Sparse-Grid Approach for Nonlinear Filtering Problems Based on Adaptive-Domain of the Zakai Equation Approximations. SIAM/ASA J. Uncertain. Quantification Feng Bao, Yanzhao Cao, Clayton G. Webster, Guannan Zhang