Qifeng Liao - RankMe

40 papers A 1Journal 39

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	An alternating low-rank projection approach for partial differential equations with random inputs. J. Comput. Phys. Guanjie Wang, Qifeng Liao
2025	J	`jnl`	A conditional normalizing flow for domain decomposed uncertainty quantification. J. Comput. Appl. Math. Sen Li, Ke Li, Yu Liu, Qifeng Liao
2025	J	`jnl`	Adaptive Deep Density Approximation for Stochastic Dynamical Systems. J. Sci. Comput. Junjie He, Qifeng Liao, Xiaoliang Wan
2025	J	`jnl`	Adaptive Probability Flow Residual Minimization for High-Dimensional Fokker-Planck Equations. CoRR Xiaolong Wu, Qifeng Liao
2025	A	`conf`	D-LUT: Photorealistic Style Transfer via Diffusion Process. WACV Mujing Li, Guanjie Wang, Xingguang Zhang, Qifeng Liao, Chenxi Xiao
2024	J	`jnl`	A conditional normalizing flow for domain decomposed uncertainty quantification. CoRR Sen Li, Ke Li, Yu Liu, Qifeng Liao
2024	J	`jnl`	Adaptive deep density approximation for stochastic dynamical systems. CoRR Junjie He, Qifeng Liao, Xiaoliang Wan
2024	J	`jnl`	An Adaptive ANOVA Stochastic Galerkin Method for Partial Differential Equations with High-dimensional Random Inputs. J. Sci. Comput. Guanjie Wang, Smita Sahu, Qifeng Liao
2024	J	`jnl`	An alternating low-rank projection approach for partial differential equations with random inputs. CoRR Guanjie Wang, Qifeng Liao
2024	J	`jnl`	Domain-decomposed Bayesian inversion based on local Karhunen-Loève expansions. J. Comput. Phys. Zhihang Xu, Qifeng Liao, Jinglai Li
2024	J	`jnl`	Reduced basis stochastic Galerkin methods for partial differential equations with random inputs. Appl. Math. Comput. Guanjie Wang, Qifeng Liao
2023	J	`jnl`	A deep domain decomposition method based on Fourier features. J. Comput. Appl. Math. Sen Li, Yingzhi Xia, Yu Liu, Qifeng Liao
2023	J	`jnl`	A domain-decomposed VAE method for Bayesian inverse problems. CoRR Zhihang Xu, Yingzhi Xia, Qifeng Liao
2023	J	`jnl`	An adaptive ANOVA stochastic Galerkin method for partial differential equations with random inputs. CoRR Guanjie Wang, Smita Sahu, Qifeng Liao
2023	J	`jnl`	Dimension-reduced KRnet maps for high-dimensional Bayesian inverse problems. CoRR Yani Feng, Kejun Tang, Xiaoliang Wan, Qifeng Liao
2023	J	`jnl`	Rank-Adaptive Tensor Completion Based on Tucker Decomposition. Entropy Siqi Liu, Xiaoyu Shi, Qifeng Liao
2023	J	`jnl`	Robin-type domain decomposition with stabilized mixed approximation for incompressible flow. Comput. Math. Appl. Yani Feng, Qifeng Liao, David J. Silvester
2023	J	`jnl`	Streaming probabilistic tensor train decomposition. CoRR Yunyu Huang, Yani Feng, Qifeng Liao
2023	J	`jnl`	VI-DGP: A Variational Inference Method with Deep Generative Prior for Solving High-Dimensional Inverse Problems. J. Sci. Comput. Yingzhi Xia, Qifeng Liao, Jinglai Li
2023	J	`jnl`	VI-DGP: A variational inference method with deep generative prior for solving high-dimensional inverse problems. CoRR Yingzhi Xia, Qifeng Liao, Jinglai Li
2022	J	`jnl`	A Stochastic Discrete Empirical Interpolation Approach for Parameterized Systems. Symmetry Daheng Cai, Chengbin Yao, Qifeng Liao
2022	J	`jnl`	A deep domain decomposition method based on Fourier features. CoRR Sen Li, Yingzhi Xia, Yu Liu, Qifeng Liao
2022	J	`jnl`	Adaptive deep density approximation for Fokker-Planck equations. J. Comput. Phys. Kejun Tang, Xiaoliang Wan, Qifeng Liao
2022	J	`jnl`	Deep neural network based adaptive learning for switched systems. CoRR Junjie He, Zhihang Xu, Qifeng Liao
2022	J	`jnl`	Domain-decomposed Bayesian inversion based on local Karhunen-Loève expansions. CoRR Zhihang Xu, Qifeng Liao, Jinglai Li
2022	J	`jnl`	Reduced basis stochastic Galerkin methods for partial differential equations with random inputs. CoRR Guanjie Wang, Qifeng Liao
2021	J	`jnl`	Adaptive deep density approximation for Fokker-Planck equations. CoRR Kejun Tang, Xiaoliang Wan, Qifeng Liao
2020	J	`jnl`	ANOVA Gaussian process modeling for high-dimensional stochastic computational models. J. Comput. Phys. Chen Chen, Qifeng Liao
2020	J	`jnl`	D3M: A Deep Domain Decomposition Method for Partial Differential Equations. IEEE Access Ke Li, Kejun Tang, Tianfan Wu, Qifeng Liao
2020	J	`jnl`	Gaussian Process Based Expected Information Gain Computation for Bayesian Optimal Design. Entropy Zhihang Xu, Qifeng Liao
2020	J	`jnl`	Rank adaptive tensor recovery based model reduction for partial differential equations with high-dimensional random inputs. J. Comput. Phys. Kejun Tang, Qifeng Liao
2020	J	`jnl`	Tensor Train Random Projection. CoRR Yani Feng, Kejun Tang, Lianxing He, Pingqiang Zhou, Qifeng Liao
2019	J	`jnl`	A Hierarchical Neural Hybrid Method for Failure Probability Estimation. IEEE Access Ke Li, Kejun Tang, Jinglai Li, Tianfan Wu, Qifeng Liao
2019	J	`jnl`	A hierarchical neural hybrid method for failure probability estimation. CoRR Ke Li, Kejun Tang, Jinglai Li, Tianfan Wu, Qifeng Liao
2019	J	`jnl`	ANOVA Gaussian process modeling for high-dimensional stochastic computational models. CoRR Chen Chen, Qifeng Liao
2019	J	`jnl`	An adaptive reduced basis ANOVA method for high-dimensional Bayesian inverse problems. J. Comput. Phys. Qifeng Liao, Jinglai Li
2019	J	`jnl`	D3M: A deep domain decomposition method for partial differential equations. CoRR Ke Li, Kejun Tang, Tianfan Wu, Qifeng Liao
2016	J	`jnl`	Reduced basis ANOVA methods for partial differential equations with high-dimensional random inputs. J. Comput. Phys. Qifeng Liao, Guang Lin
2015	J	`jnl`	A Domain Decomposition Approach for Uncertainty Analysis. SIAM J. Sci. Comput. Qifeng Liao, Karen Willcox
2013	J	`jnl`	Reduced Basis Collocation Methods for Partial Differential Equations with Random Coefficients. SIAM/ASA J. Uncertain. Quantification Howard C. Elman, Qifeng Liao