Výsledky vyhledávání

Report

Restoring the Discontinuous Heat Equation Source Using Sparse Boundary Data and Dynamic Sensors

Autor: Lin, Guang, Ou, Na, Zhang, Zecheng, Zhang, Zhidong

This study focuses on addressing the inverse source problem associated with the parabolic equation. We rely on sparse boundary flux data as our measurements, which are acquired from a restricted section of the boundary. While it has been established

Externí odkaz: http://arxiv.org/abs/2310.01541

Zobrazit plný text záznamu

Akademický článek

A replica exchange preconditioned Crank-Nicolson Langevin dynamic MCMC method with multi-variance strategy for Bayesian inverse problems

Autor: Ou, Na, Zhang, Zecheng, Lin, Guang

Publikováno v: In Journal of Computational Physics 1 August 2024 510

Zobrazit plný text záznamu

Report

Bayesian identification of discontinuous fields with an ensemble-based variable separation multiscale method

Autor: Ou, Na, Lin, Guang, Jiang, Lijian

This work presents a multiscale model reduction approach to discontinuous fields identification problems in the framework of Bayesian inference. An ensemble-based variable separation (VS) method is proposed to approximate multiscale basis functions u

Externí odkaz: http://arxiv.org/abs/1809.07994

Zobrazit plný text záznamu

Report

A two-stage ensemble Kalman filter based on multiscale model reduction for inverse problems in time fractional diffusion-wave equations

Autor: Ba, Yuming, Jiang, Lijian, Ou, Na

Ensemble Kalman filter (EnKF) has been widely used in state estimation and parameter estimation for the dynamic system where observational data is obtained sequentially in time. To reduce uncertainty and accelerate posterior inference, a two-stage en

Externí odkaz: http://arxiv.org/abs/1802.10480

Zobrazit plný text záznamu

Akademický článek

Large-scale networks underlie cognitive insight differs between untreated adolescents ongoing their first schizophrenic episode and their reference non-schizophrenic mates

Autor: Ji, Ruofei, Zhou, Ming, Ou, Na, Chen, Hudan, Li, Yang, Zhuo, Lihua, Huang, Xiaoqi, Huang, Guoping

Publikováno v: In Heliyon October 2022 8(10)

Zobrazit plný text záznamu

Report

Bayesian inference using intermediate distribution based on coarse multiscale model for time fractional diffusion equation

Autor: Jiang, Lijian, Ou, Na

In the paper, we present a strategy for accelerating posterior inference for unknown inputs in time fractional diffusion models. In many inference problems, the posterior may be concentrated in a small portion of the entire prior support. It will be

Externí odkaz: http://arxiv.org/abs/1706.10224

Zobrazit plný text záznamu

Akademický článek

Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.

Report

Multiscale model reduction method for Bayesian inverse problems of subsurface flow

Autor: Jiang, Lijian, Ou, Na

This work presents a model reduction approach to the inverse problem in the application of subsurface flows. For the Bayesian inverse problem, the forward model needs to be repeatedly computed for a large number of samples to get a stationary chain.

Externí odkaz: http://arxiv.org/abs/1604.00138

Zobrazit plný text záznamu