T
Tao Zhou
Researcher at Chinese Academy of Sciences
Publications - 90
Citations - 1833
Tao Zhou is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: Uncertainty quantification & Stochastic differential equation. The author has an hindex of 22, co-authored 85 publications receiving 1255 citations. Previous affiliations of Tao Zhou include École Polytechnique Fédérale de Lausanne.
Papers
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On Energy Dissipation Theory and Numerical Stability for Time-Fractional Phase-Field Equations
Tao Tang,Haijun Yu,Tao Zhou +2 more
TL;DR: It is proved for the first time that the time-fractional phase field models indeed admit an energy dissipation law of an integral type in the discrete level, and proposes a class of finite difference schemes that can inherit the theoretical energy stability.
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A second-order and nonuniform time-stepping maximum-principle preserving scheme for time-fractional Allen-Cahn equations
TL;DR: In this article, a second-order non-uniform time-stepping scheme for the time-fractional Allen-Cahn equation is proposed, which preserves the discrete maximum principle, and by using the convolution structure of consistency error, they present sharp maximum-norm error estimates which reflect the temporal regularity.
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New Kinds of High-Order Multistep Schemes for Coupled Forward Backward Stochastic Differential Equations
Weidong Zhao,Yu Fu,Tao Zhou +2 more
TL;DR: Based on the FBSDEs theory, two reference ordinary differential equations are derived from the backward SDE, which contain the conditional expectations and their derivatives, and high-order multistep schemes are obtained by carefully approximating the conditional expectation and the derivatives, in the reference ODEs.
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A Christoffel function weighted least squares algorithm for collocation approximations
TL;DR: This work proposes an algorithm for the Monte Carlo solution of least-squares polynomial approximation problems in a collocation frame- work, and presents theoretical analysis to motivate the algorithm, and numerical results that show the method is superior to standard Monte Carlo methods in many situations of interest.
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A Generalized Sampling and Preconditioning Scheme for Sparse Approximation of Polynomial Chaos Expansions
TL;DR: In this article, the authors proposed an algorithm for recovering sparse orthogonal polynomial expansions via collocation, where the weights of the diagonal preconditioning matrix are given by evaluations of the Christoffel function.