Kejun Tang

According to our database1, Kejun Tang authored at least 12 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
AONN: An Adjoint-Oriented Neural Network Method for All-At-Once Solutions of Parametric Optimal Control Problems.
SIAM J. Sci. Comput., February, 2024

Deep adaptive sampling for surrogate modeling without labeled data.
CoRR, 2024

2023
DAS-PINNs: A deep adaptive sampling method for solving high-dimensional partial differential equations.
J. Comput. Phys., March, 2023

Adversarial Adaptive Sampling: Unify PINN and Optimal Transport for the Approximation of PDEs.
CoRR, 2023

Dimension-reduced KRnet maps for high-dimensional Bayesian inverse problems.
CoRR, 2023

2022
Adaptive deep density approximation for Fokker-Planck equations.
J. Comput. Phys., 2022

2021
DAS: A deep adaptive sampling method for solving partial differential equations.
CoRR, 2021

Augmented KRnet for density estimation and approximation.
CoRR, 2021

2020
Rank adaptive tensor recovery based model reduction for partial differential equations with high-dimensional random inputs.
J. Comput. Phys., 2020

Tensor Train Random Projection.
CoRR, 2020

D3M: A Deep Domain Decomposition Method for Partial Differential Equations.
IEEE Access, 2020

2019
A Hierarchical Neural Hybrid Method for Failure Probability Estimation.
IEEE Access, 2019


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