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ORCIDLijian Jiang
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2020 – today
- 2024
[j36]Xuehan Zhang, Lijian Jiang
:
Conditional variational autoencoder with Gaussian process regression recognition for parametric models. J. Comput. Appl. Math. 438: 115532 (2024)- [j35]Xiaofei Guan, Lijian Jiang, Yajun Wang:
Regularized coupling multiscale method for thermomechanical coupled problems. J. Comput. Phys. 499: 112737 (2024) - [j34]Ningxin Liu, Lijian Jiang:
Perron-Frobenius Operator Filter for Stochastic Dynamical Systems. SIAM/ASA J. Uncertain. Quantification 12(1): 182-211 (2024) - [i9]Xiaofei Guan, Lijian Jiang, Yajun Wang, Zihao Yang:
Localized subspace iteration methods for elliptic multiscale problems. CoRR abs/2406.09789 (2024) - [i8]Xuhan Zhang, Lijian Jiang:
Convolutional neural network based reduced order modeling for multiscale problems. CoRR abs/2406.16328 (2024) - [i7]Dengfei Zeng, Lijian Jiang:
Ensemble Transport Filter via Optimized Maximum Mean Discrepancy. CoRR abs/2407.11518 (2024) - 2023
- [j33]Xiaofei Guan, Lijian Jiang, Yajun Wang:
Multiscale model reduction for stochastic elasticity problems using ensemble variable-separated method. J. Comput. Appl. Math. 421: 114895 (2023) - [j32]Mengnan Li, Lijian Jiang:
Data-driven reduced-order modeling for nonautonomous dynamical systems in multiscale media. J. Comput. Phys. 474: 111799 (2023) - [j31]Meng Zhao, Lijian Jiang:
Data-driven probability density forecast for stochastic dynamical systems. J. Comput. Phys. 492: 112422 (2023) - [i6]Ningxin Liu, Lijian Jiang:
Perron-Frobenius operator filter for stochastic dynamical systems. CoRR abs/2301.03080 (2023) - [i5]Xiaofei Guan, Lijian Jiang, Yajun Wang, Zihao Yang:
A coupling generalized multiscale finite element method for coupled thermomechanical problems. CoRR abs/2302.01674 (2023) - [i4]Xuehan Zhang, Lijian Jiang:
Conditional variational autoencoder with Gaussian process regression recognition for parametric models. CoRR abs/2305.09625 (2023) - 2022
- [j30]Yuming Ba, Lijian Jiang:
A residual-driven adaptive Gaussian mixture approximation for Bayesian inverse problems. J. Comput. Appl. Math. 399: 113707 (2022) - [j29]Lijian Jiang, Ningxin Liu:
Correcting noisy dynamic mode decomposition with Kalman filters. J. Comput. Phys. 461: 111175 (2022) - [j28]Lijian Jiang, Mengnan Li, Meng Zhao:
Online Multiscale Model Reduction for Nonlinear Stochastic PDEs with Multiplicative Noise. Multiscale Model. Simul. 20(3): 1063-1092 (2022) - [i3]Lijian Jiang, Mengnan Li, Meng Zhao:
Online multiscale model reduction for nonlinear stochastic PDEs with multiplicative noise. CoRR abs/2204.11712 (2022) - [i2]Mengnan Li, Lijian Jiang:
Reduced-order modeling for Koopman operators of nonautonomous dynamic systems in multiscale media. CoRR abs/2204.13180 (2022) - [i1]Meng Zhao, Lijian Jiang:
Data-driven probability density forecast for stochastic dynamical systems. CoRR abs/2210.03418 (2022) - 2021
- [j27]Xiaoyan Song, Guang-Hui Zheng, Lijian Jiang:
Variational Bayesian inversion for the reaction coefficient in space-time nonlocal diffusion equations. Adv. Comput. Math. 47(3): 31 (2021) - [j26]Shan Zhang, Xiaofei Guan, Lijian Jiang:
Convergence analysis of constraint energy minimizing generalized multiscale finite element method for a linear stochastic parabolic partial differential equation driven by additive noises. J. Comput. Appl. Math. 389: 113328 (2021) - [j25]Yuming Ba, Lijian Jiang:
A two-stage variable-separation Kalman filter for data assimilation. J. Comput. Phys. 434: 110244 (2021) - [j24]Mengnan Li, Lijian Jiang:
Deep learning nonlinear multiscale dynamic problems using Koopman operator. J. Comput. Phys. 446: 110660 (2021) - 2020
- [j23]Xiaoyan Song, Lijian Jiang, Guang-Hui Zheng:
Implicit sampling for hierarchical Bayesian inversion and applications in fractional multiscale diffusion models. J. Comput. Appl. Math. 375: 112826 (2020) - [j22]Na Ou, Guang Lin, Lijian Jiang:
A Low-Rank Approximated Multiscale Method for Pdes With Random Coefficients. Multiscale Model. Simul. 18(4): 1595-1620 (2020)
2010 – 2019
- 2019
- [j21]Xiaoyan Song, Guang-Hui Zheng, Lijian Jiang:
Identification of the reaction coefficient in time fractional diffusion equations. J. Comput. Appl. Math. 345: 295-309 (2019) - [j20]Qiuqi Li, Lijian Jiang:
A multiscale virtual element method for elliptic problems in heterogeneous porous media. J. Comput. Phys. 388: 394-415 (2019) - [j19]Mengnan Li, Eric T. Chung, Lijian Jiang:
A Constraint Energy Minimizing Generalized Multiscale Finite Element Method for Parabolic Equations. Multiscale Model. Simul. 17(3): 996-1018 (2019) - 2018
- [j18]Lingling Ma, Lijian Jiang:
Convergence analysis for GMsFEM approximation of elliptic eigenvalue problems. J. Comput. Appl. Math. 327: 109-126 (2018) - [j17]Lijian Jiang, Qiuqi Li:
Model reduction method using variable-separation for stochastic saddle point problems. J. Comput. Phys. 354: 43-66 (2018) - [j16]Yuming Ba, Lijian Jiang, Na Ou:
A two-stage ensemble Kalman filter based on multiscale model reduction for inverse problems in time fractional diffusion-wave equations. J. Comput. Phys. 374: 300-330 (2018) - [j15]Lijian Jiang, Na Ou:
Bayesian Inference Using Intermediate Distribution Based on Coarse Multiscale Model for Time Fractional Diffusion Equations. Multiscale Model. Simul. 16(1): 327-355 (2018) - [j14]Fuchen Chen, Eric T. Chung, Lijian Jiang:
Adaptive Least-Squares Mixed Generalized Multiscale Finite Element Methods. Multiscale Model. Simul. 16(2): 1034-1058 (2018) - 2017
- [j13]Lijian Jiang, Na Ou:
Multiscale model reduction method for Bayesian inverse problems of subsurface flow. J. Comput. Appl. Math. 319: 188-209 (2017) - [j12]Lijian Jiang, Qiuqi Li:
Model's sparse representation based on reduced mixed GMsFE basis methods. J. Comput. Phys. 338: 285-312 (2017) - [j11]Qiuqi Li, Lijian Jiang:
A Novel Variable-Separation Method Based on Sparse and Low Rank Representation for Stochastic Partial Differential Equations. SIAM J. Sci. Comput. 39(6) (2017) - 2016
- [j10]Huailing Song, Lijian Jiang, Qiuqi Li:
A reduced order method for Allen-Cahn equations. J. Comput. Appl. Math. 292: 213-229 (2016) - [j9]Lijian Jiang, Qiuqi Li:
Reduced multiscale finite element basis methods for elliptic PDEs with parameterized inputs. J. Comput. Appl. Math. 301: 101-120 (2016) - 2015
- [j8]Lijian Jiang, Xinping Li:
Multi-element least square HDMR methods and their applications for stochastic multiscale model reduction. J. Comput. Phys. 294: 439-461 (2015) - 2014
- [j7]Huailing Song, Lijian Jiang, Gaojie Chen:
Convergence analysis of hybrid expanded mixed finite element method for elliptic equations. Comput. Math. Appl. 68(10): 1205-1219 (2014) - [j6]Lijian Jiang, J. David Moulton, Jia Wei:
A Hybrid HDMR for Mixed Multiscale Finite Element Methods with Application to Flows in Random Porous Media. Multiscale Model. Simul. 12(1): 119-151 (2014) - 2013
- [j5]Xinguang He, Lijian Jiang:
An upscaling method using coefficient splitting and its applications to elliptic PDEs. Comput. Math. Appl. 65(4): 712-730 (2013) - 2012
- [j4]Lijian Jiang, Dylan Copeland, J. David Moulton:
Expanded Mixed Multiscale Finite Element Methods and Their Applications for Flows in Porous Media. Multiscale Model. Simul. 10(2): 418-450 (2012) - [j3]Lijian Jiang, Michael Presho:
A Resourceful Splitting Technique with Applications to Deterministic and Stochastic Multiscale Finite Element Methods. Multiscale Model. Simul. 10(3): 954-985 (2012)
2000 – 2009
- 2009
- [j2]Lijian Jiang, Craig C. Douglas:
An analysis of 4D variational data assimilation and its application. Computing 84(1-2): 97-120 (2009) - 2008
- [j1]Jørg E. Aarnes, Yalchin Efendiev, Lijian Jiang:
Mixed Multiscale Finite Element Methods Using Limited Global Information. Multiscale Model. Simul. 7(2): 655-676 (2008)
Coauthor Index
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