Mixed Multiscale Finite Element Methods Using Limited Global Information. - Jørg E. Aarnes; Yalchin Efendiev; Lijian Jiang (Multiscale Model. Simul., 2008)

An analysis of 4D variational data assimilation and its application. - Lijian Jiang; Craig C. Douglas (Computing, 2009)

Expanded Mixed Multiscale Finite Element Methods and Their Applications for Flows in Porous Media. - Lijian Jiang; Dylan Copeland; J. David Moulton (Multiscale Model. Simul., 2012)

A Resourceful Splitting Technique with Applications to Deterministic and Stochastic Multiscale Finite Element Methods. - Lijian Jiang; Michael Presho (Multiscale Model. Simul., 2012)

An upscaling method using coefficient splitting and its applications to elliptic PDEs. - Xinguang He; Lijian Jiang (Comput. Math. Appl., 2013)

Convergence analysis of hybrid expanded mixed finite element method for elliptic equations. - Huailing Song; Lijian Jiang; Gaojie Chen (Comput. Math. Appl., 2014)

A Hybrid HDMR for Mixed Multiscale Finite Element Methods with Application to Flows in Random Porous Media. - Lijian Jiang; J. David Moulton; Jia Wei (Multiscale Model. Simul., 2014)

Multi-element least square HDMR methods and their applications for stochastic multiscale model reduction. - Lijian Jiang; Xinping Li (J. Comput. Phys., 2015)

Reduced multiscale finite element basis methods for elliptic PDEs with parameterized inputs. - Lijian Jiang; Qiuqi Li (J. Comput. Appl. Math., 2016)

A reduced order method for Allen-Cahn equations. - Huailing Song; Lijian Jiang; Qiuqi Li (J. Comput. Appl. Math., 2016)

Multiscale model reduction method for Bayesian inverse problems of subsurface flow. - Lijian Jiang; Na Ou (J. Comput. Appl. Math., 2017)

Model's sparse representation based on reduced mixed GMsFE basis methods. - Lijian Jiang; Qiuqi Li (J. Comput. Phys., 2017)

A Novel Variable-Separation Method Based on Sparse and Low Rank Representation for Stochastic Partial Differential Equations. - Qiuqi Li; Lijian Jiang (SIAM J. Sci. Comput., 2017)

Convergence analysis for GMsFEM approximation of elliptic eigenvalue problems. - Lingling Ma; Lijian Jiang (J. Comput. Appl. Math., 2018)

A two-stage ensemble Kalman filter based on multiscale model reduction for inverse problems in time fractional diffusion-wave equations. - Yuming Ba; Lijian Jiang; Na Ou (J. Comput. Phys., 2018)

Model reduction method using variable-separation for stochastic saddle point problems. - Lijian Jiang; Qiuqi Li (J. Comput. Phys., 2018)

Adaptive Least-Squares Mixed Generalized Multiscale Finite Element Methods. - Fuchen Chen; Eric T. Chung 001; Lijian Jiang (Multiscale Model. Simul., 2018)

Bayesian Inference Using Intermediate Distribution Based on Coarse Multiscale Model for Time Fractional Diffusion Equations. - Lijian Jiang; Na Ou (Multiscale Model. Simul., 2018)

Identification of the reaction coefficient in time fractional diffusion equations. - Xiaoyan Song; Guang-Hui Zheng; Lijian Jiang (J. Comput. Appl. Math., 2019)

A multiscale virtual element method for elliptic problems in heterogeneous porous media. - Qiuqi Li; Lijian Jiang (J. Comput. Phys., 2019)

A Constraint Energy Minimizing Generalized Multiscale Finite Element Method for Parabolic Equations. - Mengnan Li; Eric T. Chung 001; Lijian Jiang (Multiscale Model. Simul., 2019)

Implicit sampling for hierarchical Bayesian inversion and applications in fractional multiscale diffusion models. - Xiaoyan Song; Lijian Jiang; Guang-Hui Zheng (J. Comput. Appl. Math., 2020)

A Low-Rank Approximated Multiscale Method for Pdes With Random Coefficients. - Na Ou; Guang Lin 001; Lijian Jiang (Multiscale Model. Simul., 2020)

Variational Bayesian inversion for the reaction coefficient in space-time nonlocal diffusion equations. - Xiaoyan Song; Guang-Hui Zheng; Lijian Jiang (Adv. Comput. Math., 2021)

Convergence analysis of constraint energy minimizing generalized multiscale finite element method for a linear stochastic parabolic partial differential equation driven by additive noises. - Shan Zhang; Xiaofei Guan; Lijian Jiang (J. Comput. Appl. Math., 2021)

A two-stage variable-separation Kalman filter for data assimilation. - Yuming Ba; Lijian Jiang (J. Comput. Phys., 2021)

Deep learning nonlinear multiscale dynamic problems using Koopman operator. - Mengnan Li; Lijian Jiang (J. Comput. Phys., 2021)

Reduced-order modeling for Koopman operators of nonautonomous dynamic systems in multiscale media. - Mengnan Li; Lijian Jiang (CoRR, 2022)

A residual-driven adaptive Gaussian mixture approximation for Bayesian inverse problems. - Yuming Ba; Lijian Jiang (J. Comput. Appl. Math., 2022)

Correcting noisy dynamic mode decomposition with Kalman filters. - Lijian Jiang; Ningxin Liu (J. Comput. Phys., 2022)

Online Multiscale Model Reduction for Nonlinear Stochastic PDEs with Multiplicative Noise. - Lijian Jiang; Mengnan Li; Meng Zhao (Multiscale Model. Simul., 2022)

A coupling generalized multiscale finite element method for coupled thermomechanical problems. - Xiaofei Guan; Lijian Jiang; Yajun Wang; Zihao Yang (CoRR, 2023)

Multiscale model reduction for stochastic elasticity problems using ensemble variable-separated method. - Xiaofei Guan; Lijian Jiang; Yajun Wang (J. Comput. Appl. Math., 2023)

Data-driven reduced-order modeling for nonautonomous dynamical systems in multiscale media. - Mengnan Li; Lijian Jiang (J. Comput. Phys., 2023)

Data-driven probability density forecast for stochastic dynamical systems. - Meng Zhao; Lijian Jiang (J. Comput. Phys., 2023)

Localized subspace iteration methods for elliptic multiscale problems. - Xiaofei Guan; Lijian Jiang; Yajun Wang; Zihao Yang (CoRR, 2024)

Convolutional neural network based reduced order modeling for multiscale problems. - Xuhan Zhang; Lijian Jiang (CoRR, 2024)

Ensemble Transport Filter via Optimized Maximum Mean Discrepancy. - Dengfei Zeng; Lijian Jiang (CoRR, 2024)

Estimate of Koopman modes and eigenvalues with Kalman Filter. - Ningxin Liu; Shuigen Liu; Xin T. Tong; Lijian Jiang (CoRR, 2024)

Regularized coupling multiscale method for thermomechanical coupled problems. - Xiaofei Guan; Lijian Jiang; Yajun Wang (J. Comput. Phys., 2024)

Conditional variational autoencoder with Gaussian process regression recognition for parametric models. - Xuehan Zhang; Lijian Jiang (J. Comput. Appl. Math., 2024)

Perron-Frobenius Operator Filter for Stochastic Dynamical Systems. - Ningxin Liu; Lijian Jiang (SIAM/ASA J. Uncertain. Quantification, 2024)

Model free data assimilation with Takens embedding. - Ziyi Wang; Lijian Jiang (J. Comput. Appl. Math., 2025)

Convolutional neural network based reduced order modeling for multiscale problems. - Xuehan Zhang; Lijian Jiang (J. Comput. Phys., 2025)