Kejun Tang - RankMe

25 papers A* 1Journal 24

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Estimating committor functions via deep adaptive sampling on rare transition paths. J. Comput. Phys. Yueyang Wang, Kejun Tang, Xili Wang, Xiaoliang Wan, Weiqing Ren, Chao Yang
2026	J	`jnl`	Moving sample method for solving time-dependent partial differential equations. CoRR Beining Xu, Haijun Yu, Jiayu Zhai, Kejun Tang, Xiaoliang Wan
2025	J	`jnl`	APTT: Accuracy-Preserved Tensor-Train Method for the Boltzmann-BGK Equation. SIAM J. Sci. Comput. Zhitao Zhu, Chuanfu Xiao, Kejun Tang, Jizu Huang, Chao Yang
2025	J	`jnl`	Estimating Committor Functions via Deep Adaptive Sampling on Rare Transition Paths. CoRR Yueyang Wang, Kejun Tang, Xili Wang, Xiaoliang Wan, Weiqing Ren, Chao Yang
2025	J	`jnl`	Functional tensor train neural network for solving high-dimensional PDEs. CoRR Yani Feng, Michael K. Ng, Kejun Tang, Zhiwen Zhang
2025	J	`jnl`	Provable Low-Rank Tensor-Train Approximations in the Inverse of Large-Scale Structured Matrices. CoRR Chuanfu Xiao, Kejun Tang, Zhitao Zhu
2024	J	`jnl`	AONN: An Adjoint-Oriented Neural Network Method for All-At-Once Solutions of Parametric Optimal Control Problems. SIAM J. Sci. Comput. Pengfei Yin, Guangqiang Xiao, Kejun Tang, Chao Yang
2024	J	`jnl`	APTT: An accuracy-preserved tensor-train method for the Boltzmann-BGK equation. CoRR Zhitao Zhu, Chuanfu Xiao, Kejun Tang, Jizu Huang, Chao Yang
2024	A*	`conf`	Adversarial Adaptive Sampling: Unify PINN and Optimal Transport for the Approximation of PDEs. ICLR Kejun Tang, Jiayu Zhai, Xiaoliang Wan, Chao Yang
2024	J	`jnl`	Deep Adaptive Sampling for Surrogate Modeling Without Labeled Data. J. Sci. Comput. Xili Wang, Kejun Tang, Jiayu Zhai, Xiaoliang Wan, Chao Yang
2024	J	`jnl`	Deep adaptive sampling for surrogate modeling without labeled data. CoRR Xili Wang, Kejun Tang, Jiayu Zhai, Xiaoliang Wan, Chao Yang
2024	J	`jnl`	Trajectory optimization for automated tape placement on triangular mesh surfaces considering gap requirements. J. Comput. Des. Eng. Peng Zhang, Yuyu Li, Kejun Tang, Lairong Yin, Long Huang, HongBing Wang
2023	J	`jnl`	Adversarial Adaptive Sampling: Unify PINN and Optimal Transport for the Approximation of PDEs. CoRR Kejun Tang, Jiayu Zhai, Xiaoliang Wan, Chao Yang
2023	J	`jnl`	DAS-PINNs: A deep adaptive sampling method for solving high-dimensional partial differential equations. J. Comput. Phys. Kejun Tang, Xiaoliang Wan, Chao Yang
2023	J	`jnl`	Dimension-reduced KRnet maps for high-dimensional Bayesian inverse problems. CoRR Yani Feng, Kejun Tang, Xiaoliang Wan, Qifeng Liao
2022	J	`jnl`	Adaptive deep density approximation for Fokker-Planck equations. J. Comput. Phys. Kejun Tang, Xiaoliang Wan, Qifeng Liao
2021	J	`jnl`	Adaptive deep density approximation for Fokker-Planck equations. CoRR Kejun Tang, Xiaoliang Wan, Qifeng Liao
2021	J	`jnl`	Augmented KRnet for density estimation and approximation. CoRR Xiaoliang Wan, Kejun Tang
2021	J	`jnl`	DAS: A deep adaptive sampling method for solving partial differential equations. CoRR Kejun Tang, Xiaoliang Wan, Chao Yang
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`	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`	D3M: A deep domain decomposition method for partial differential equations. CoRR Ke Li, Kejun Tang, Tianfan Wu, Qifeng Liao