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ORCIDKejun Tang
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2020 – today
- 2024
[j8]Peng Zhang, Yuyu Li, Kejun Tang, Lairong Yin, Long Huang, Hongbing Wang:
Trajectory optimization for automated tape placement on triangular mesh surfaces considering gap requirements. J. Comput. Des. Eng. 11(2): 230-252 (2024)- [j7]Xili Wang, Kejun Tang, Jiayu Zhai, Xiaoliang Wan, Chao Yang:
Deep Adaptive Sampling for Surrogate Modeling Without Labeled Data. J. Sci. Comput. 101(3): 77 (2024) - [j6]Pengfei Yin, Guangqiang Xiao, Kejun Tang, Chao Yang
:
AONN: An Adjoint-Oriented Neural Network Method for All-At-Once Solutions of Parametric Optimal Control Problems. SIAM J. Sci. Comput. 46(1): 127- (2024) - [c1]Kejun Tang, Jiayu Zhai, Xiaoliang Wan, Chao Yang:
Adversarial Adaptive Sampling: Unify PINN and Optimal Transport for the Approximation of PDEs. ICLR 2024 - [i10]Xili Wang, Kejun Tang, Jiayu Zhai, Xiaoliang Wan, Chao Yang:
Deep adaptive sampling for surrogate modeling without labeled data. CoRR abs/2402.11283 (2024) - [i9]Zhitao Zhu, Chuanfu Xiao, Kejun Tang, Jizu Huang, Chao Yang:
APTT: An accuracy-preserved tensor-train method for the Boltzmann-BGK equation. CoRR abs/2405.12524 (2024) - 2023
- [j5]Kejun Tang, Xiaoliang Wan, Chao Yang:
DAS-PINNs: A deep adaptive sampling method for solving high-dimensional partial differential equations. J. Comput. Phys. 476: 111868 (2023) - [i8]Yani Feng, Kejun Tang, Xiaoliang Wan, Qifeng Liao:
Dimension-reduced KRnet maps for high-dimensional Bayesian inverse problems. CoRR abs/2303.00573 (2023) - [i7]Kejun Tang, Jiayu Zhai, Xiaoliang Wan, Chao Yang:
Adversarial Adaptive Sampling: Unify PINN and Optimal Transport for the Approximation of PDEs. CoRR abs/2305.18702 (2023) - 2022
- [j4]Kejun Tang, Xiaoliang Wan, Qifeng Liao:
Adaptive deep density approximation for Fokker-Planck equations. J. Comput. Phys. 457: 111080 (2022) - 2021
- [i6]Kejun Tang, Xiaoliang Wan, Qifeng Liao:
Adaptive deep density approximation for Fokker-Planck equations. CoRR abs/2103.11181 (2021) - [i5]Xiaoliang Wan, Kejun Tang:
Augmented KRnet for density estimation and approximation. CoRR abs/2105.12866 (2021) - [i4]Kejun Tang, Xiaoliang Wan, Chao Yang:
DAS: A deep adaptive sampling method for solving partial differential equations. CoRR abs/2112.14038 (2021) - 2020
- [j3]Ke Li, Kejun Tang, Tianfan Wu, Qifeng Liao:
D3M: A Deep Domain Decomposition Method for Partial Differential Equations. IEEE Access 8: 5283-5294 (2020) - [j2]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) - [i3]Yani Feng, Kejun Tang, Lianxing He, Pingqiang Zhou, Qifeng Liao:
Tensor Train Random Projection. CoRR abs/2010.10797 (2020)
2010 – 2019
- 2019
- [j1]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) - [i2]Ke Li, Kejun Tang, Jinglai Li, Tianfan Wu, Qifeng Liao:
A hierarchical neural hybrid method for failure probability estimation. CoRR abs/1908.01235 (2019) - [i1]Ke Li, Kejun Tang, Tianfan Wu, Qifeng Liao:
D3M: A deep domain decomposition method for partial differential equations. CoRR abs/1909.12236 (2019)
Coauthor Index
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