Numerical approximations of exact controllability problems by optimal control problems for parabolic differential equations. - Yanzhao Cao (Appl. Math. Comput., 2001)

An Efficient Monte Carlo Method for Optimal Control Problems with Uncertainty. - Yanzhao Cao; M. Yousuff Hussaini; Thomas A. Zang (Comput. Optim. Appl., 2003)

A Hybrid Collocation Method for Volterra Integral Equations with Weakly Singular Kernels. - Yanzhao Cao; Terry Herdman; Yuesheng Xu (SIAM J. Numer. Anal., 2003)

Finite element methods for semilinear elliptic stochastic partial differential equations. - Yanzhao Cao; Hongtao Yang; Li Yin (Numerische Mathematik, 2007)

Exploitation of sensitivity derivatives via randomized quasi-Monte Carlo methods. - Yanzhao Cao; Hongmei Chi; C. Milton; Weidong Zhao (Monte Carlo Methods Appl., 2008)

A Fast Collocation Method for Solving Stochastic Integral Equations. - Yanzhao Cao; Bin Wu; Yuesheng Xu (SIAM J. Numer. Anal., 2009)

Generating Parallel Random Sequences via Parameterizing EICGs for Heterogeneous Computing Environments. - Hongmei Chi; Yanzhao Cao (ICCSA (4), 2010)

Error analysis of finite element approximations of the stochastic Stokes equations. - Yanzhao Cao; Zheng Chen; Max D. Gunzburger (Adv. Comput. Math., 2010)

Finite Element Approximations for Stokes-Darcy Flow with Beavers-Joseph Interface Conditions. - Yanzhao Cao; Max D. Gunzburger; Xiaolong Hu; Fei Hua; Xiaoming Wang 009; Weidong Zhao (SIAM J. Numer. Anal., 2010)

Robin-Robin domain decomposition methods for the steady-state Stokes-Darcy system with the Beavers-Joseph interface condition. - Yanzhao Cao; Max D. Gunzburger; Xiaoming He; Xiaoming Wang 009 (Numerische Mathematik, 2011)

Orthogonal polynomial expansions on sparse grids. - Yanzhao Cao; Ying Jiang 002; Yuesheng Xu (J. Complex., 2014)

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)

Parallel, non-iterative, multi-physics domain decomposition methods for time-dependent Stokes-Darcy systems. - Yanzhao Cao; Max D. Gunzburger; Xiaoming He; Xiaoming Wang 009 (Math. Comput., 2014)

Particle Swarm Optimization Simulation via Optimal Halton Sequences. - Ganesha Weerasinghe; Hongmei Chi; Yanzhao Cao (ICCS, 2016)

Well-posedness and a numerical study of a regularization model with adaptive nonlinear filtering for incompressible fluid flow. - Yanzhao Cao; Song Chen; Leo G. Rebholz (Comput. Math. Appl., 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 fast discrete spectral method for stochastic partial differential equations. - Yanzhao Cao; Ying Jiang 002; Yuesheng Xu (Adv. Comput. Math., 2017)

Computational singular perturbation analysis of stochastic chemical systems with stiffness. - Lijin Wang; Xiaoying Han; Yanzhao Cao; Habib N. Najm (J. Comput. Phys., 2017)

Approximating Stochastic Evolution Equations with Additive White and Rough Noises. - Yanzhao Cao; Jialin Hong; Zhihui Liu (SIAM J. Numer. Anal., 2017)

A Robust Numerical Method for the Random Interface Grating Problem via Shape Calculus, Weak Galerkin Method, and Low-Rank Approximation. - Gang Bao; Yanzhao Cao; Yongle Hao; Kai Zhang (J. Sci. Comput., 2018)

An explicit a posteriori error estimations for the cell functional minimization scheme of elliptic problems. - Li Yin; Zhiming Gao; Yanzhao Cao (J. Comput. Appl. Math., 2019)

A locking free numerical approximation for quasilinear poroelasticity problems. - Jingyuan Zhang; Chenguang Zhou; Yanzhao Cao; Amnon J. Meir (Comput. Math. Appl., 2020)

Analysis of the Stochastic Alternating Least Squares Method for the Decomposition of Random Tensors. - Yanzhao Cao; Somak Das; Luke Oeding; Hans-Werner van Wyk (CoRR, 2020)

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

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

Adaptive Gradient Descent for Optimal Control of Parabolic Equations with Random Parameters. - Yanzhao Cao; Somak Das; Hans-Werner van Wyk (CoRR, 2021)

Mean-square convergence of numerical methods for random ordinary differential equations. - Peng Wang; Yanzhao Cao; Xiaoying Han; Peter Kloeden (Numer. Algorithms, 2021)

Fast and accurate domain decomposition methods for reduced fracture models with nonconforming time grids. - Phuoc-Toan Huynh; Yanzhao Cao; Thi-Thao-Phuong Hoang (CoRR, 2022)

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

Splitting-up Spectral Method for Nonlinear Filtering Problems with Correlation Noises. - Fengshan Zhang; Yongkui Zou; Shimin Chai; Ran Zhang; Yanzhao Cao (J. Sci. Comput., 2022)

A pseudo-reversible normalizing flow for stochastic dynamical systems with various initial distributions. - Minglei Yang 005; Pengjun Wang; Diego del-Castillo-Negrete; Yanzhao Cao; 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)

Fast and Accuracy-Preserving Domain Decomposition Methods for Reduced Fracture Models with Nonconforming Time Grids. - Phuoc-Toan Huynh; Yanzhao Cao; Thi-Thao-Phuong Hoang (J. Sci. Comput., 2023)

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

A Probabilistic Scheme for Semilinear Nonlocal Diffusion Equations with Volume Constraints. - Minglei Yang 005; Guannan Zhang; Diego del-Castillo-Negrete; Yanzhao Cao (SIAM J. Numer. Anal., 2023)

Conditional Pseudo-Reversible Normalizing Flow for Surrogate Modeling in Quantifying Uncertainty Propagation. - Minglei Yang 005; Pengjun Wang; Ming Fan; Dan Lu 001; Yanzhao Cao; Guannan Zhang (CoRR, 2024)

Strong convergence of an explicit full-discrete scheme for stochastic Burgers-Huxley equation. - Yibo Wang 010; Wanrong Cao; Yanzhao Cao (CoRR, 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)

A Pseudoreversible Normalizing Flow for Stochastic Dynamical Systems with Various Initial Distributions. - Minglei Yang 005; Pengjun Wang; Diego del-Castillo-Negrete; Yanzhao Cao; Guannan Zhang (SIAM J. Sci. Comput., 2024)

Numerical analysis of a time discretized method for nonlinear filtering problem with Lévy process observations. - Fengshan Zhang; Yongkui Zou; Shimin Chai; Yanzhao Cao (Adv. Comput. Math., 2024)

Splitting finite element approximations for quasi-static electroporoelasticity equations. - Xuan Liu; Yongkui Zou; Ran Zhang; Yanzhao Cao; Amnon J. Meir (CoRR, 2025)

Learning Hamiltonian Systems with Pseudo-symplectic Neural Network. - Xupeng Cheng; Lijin Wang; Yanzhao Cao; Chen Chen (CoRR, 2025)

Weak Convergence Analysis for the Finite Element Approximation to Stochastic Allen-Cahn Equation Driven by Multiplicative White Noise. - Minxing Zhang; Yongkui Zou; Ran Zhang; Yanzhao Cao (CoRR, 2025)

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

Learning Stochastic Hamiltonian Systems via Stochastic Generating Function Neural Network. - Chen Chen; Lijin Wang; Yanzhao Cao; Xupeng Cheng (CoRR, 2025)

Generative AI Models for Learning Flow Maps of Stochastic Dynamical Systems in Bounded Domains. - Minglei Yang 005; Yanfang Liu; Diego del-Castillo-Negrete; Yanzhao Cao; Guannan Zhang (CoRR, 2025)