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2020 – today
- 2024
[j18]Guanjie Wang
, Qifeng Liao:
Reduced basis stochastic Galerkin methods for partial differential equations with random inputs. Appl. Math. Comput. 463: 128375 (2024)- [j17]Zhihang Xu, Qifeng Liao, Jinglai Li:
Domain-decomposed Bayesian inversion based on local Karhunen-Loève expansions. J. Comput. Phys. 504: 112856 (2024) - [j16]Guanjie Wang, Smita Sahu, Qifeng Liao:
An Adaptive ANOVA Stochastic Galerkin Method for Partial Differential Equations with High-dimensional Random Inputs. J. Sci. Comput. 98(1): 24 (2024) - [i15]Junjie He, Qifeng Liao, Xiaoliang Wan:
Adaptive deep density approximation for stochastic dynamical systems. CoRR abs/2405.02810 (2024) - 2023
- [j15]Yani Feng, Qifeng Liao, David J. Silvester:
Robin-type domain decomposition with stabilized mixed approximation for incompressible flow. Comput. Math. Appl. 147: 53-63 (2023) - [j14]Siqi Liu, Xiaoyu Shi, Qifeng Liao:
Rank-Adaptive Tensor Completion Based on Tucker Decomposition. Entropy 25(2): 225 (2023) - [j13]Sen Li, Yingzhi Xia, Yu Liu, Qifeng Liao:
A deep domain decomposition method based on Fourier features. J. Comput. Appl. Math. 423: 114963 (2023) - [j12]Yingzhi Xia, Qifeng Liao, Jinglai Li:
VI-DGP: A Variational Inference Method with Deep Generative Prior for Solving High-Dimensional Inverse Problems. J. Sci. Comput. 97(1): 16 (2023) - [i14]Zhihang Xu, Yingzhi Xia, Qifeng Liao:
A domain-decomposed VAE method for Bayesian inverse problems. CoRR abs/2301.05708 (2023) - [i13]Yingzhi Xia, Qifeng Liao, Jinglai Li:
VI-DGP: A variational inference method with deep generative prior for solving high-dimensional inverse problems. CoRR abs/2302.11173 (2023) - [i12]Yunyu Huang, Yani Feng, Qifeng Liao:
Streaming probabilistic tensor train decomposition. CoRR abs/2302.12148 (2023) - [i11]Yani Feng, Kejun Tang, Xiaoliang Wan, Qifeng Liao:
Dimension-reduced KRnet maps for high-dimensional Bayesian inverse problems. CoRR abs/2303.00573 (2023) - [i10]Guanjie Wang, Smita Sahu, Qifeng Liao:
An adaptive ANOVA stochastic Galerkin method for partial differential equations with random inputs. CoRR abs/2305.03939 (2023) - 2022
- [j11]Kejun Tang, Xiaoliang Wan, Qifeng Liao:
Adaptive deep density approximation for Fokker-Planck equations. J. Comput. Phys. 457: 111080 (2022) - [j10]Daheng Cai, Chengbin Yao, Qifeng Liao:
A Stochastic Discrete Empirical Interpolation Approach for Parameterized Systems. Symmetry 14(3): 556 (2022) - [i9]Sen Li, Yingzhi Xia, Yu Liu, Qifeng Liao:
A deep domain decomposition method based on Fourier features. CoRR abs/2205.01884 (2022) - [i8]Junjie He, Zhihang Xu, Qifeng Liao:
Deep neural network based adaptive learning for switched systems. CoRR abs/2207.04623 (2022) - [i7]Guanjie Wang, Qifeng Liao:
Reduced basis stochastic Galerkin methods for partial differential equations with random inputs. CoRR abs/2209.12163 (2022) - [i6]Zhihang Xu, Qifeng Liao, Jinglai Li:
Domain-decomposed Bayesian inversion based on local Karhunen-Loève expansions. CoRR abs/2211.04026 (2022) - 2021
- [i5]Kejun Tang, Xiaoliang Wan, Qifeng Liao:
Adaptive deep density approximation for Fokker-Planck equations. CoRR abs/2103.11181 (2021) - 2020
- [j9]Ke Li, Kejun Tang, Tianfan Wu, Qifeng Liao:
D3M: A Deep Domain Decomposition Method for Partial Differential Equations. IEEE Access 8: 5283-5294 (2020) - [j8]Zhihang Xu, Qifeng Liao:
Gaussian Process Based Expected Information Gain Computation for Bayesian Optimal Design. Entropy 22(2): 258 (2020) - [j7]Kejun Tang, Qifeng Liao:
Rank adaptive tensor recovery based model reduction for partial differential equations with high-dimensional random inputs. J. Comput. Phys. 409: 109326 (2020) - [j6]Chen Chen, Qifeng Liao:
ANOVA Gaussian process modeling for high-dimensional stochastic computational models. J. Comput. Phys. 416: 109519 (2020) - [i4]Yani Feng, Kejun Tang, Lianxing He, Pingqiang Zhou, Qifeng Liao:
Tensor Train Random Projection. CoRR abs/2010.10797 (2020)
2010 – 2019
- 2019
- [j5]Ke Li, Kejun Tang, Jinglai Li, Tianfan Wu, Qifeng Liao:
A Hierarchical Neural Hybrid Method for Failure Probability Estimation. IEEE Access 7: 112087-112096 (2019) - [j4]Qifeng Liao, Jinglai Li:
An adaptive reduced basis ANOVA method for high-dimensional Bayesian inverse problems. J. Comput. Phys. 396: 364-380 (2019) - [i3]Ke Li, Kejun Tang, Jinglai Li, Tianfan Wu, Qifeng Liao:
A hierarchical neural hybrid method for failure probability estimation. CoRR abs/1908.01235 (2019) - [i2]Ke Li, Kejun Tang, Tianfan Wu, Qifeng Liao:
D3M: A deep domain decomposition method for partial differential equations. CoRR abs/1909.12236 (2019) - [i1]Chen Chen, Qifeng Liao:
ANOVA Gaussian process modeling for high-dimensional stochastic computational models. CoRR abs/1911.05580 (2019) - 2016
- [j3]Qifeng Liao, Guang Lin:
Reduced basis ANOVA methods for partial differential equations with high-dimensional random inputs. J. Comput. Phys. 317: 148-164 (2016) - 2015
- [j2]Qifeng Liao, Karen Willcox:
A Domain Decomposition Approach for Uncertainty Analysis. SIAM J. Sci. Comput. 37(1) (2015) - 2013
- [j1]Howard C. Elman, Qifeng Liao:
Reduced Basis Collocation Methods for Partial Differential Equations with Random Coefficients. SIAM/ASA J. Uncertain. Quantification 1(1): 192-217 (2013)
Coauthor Index
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