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Stein variational gradient descent with local approximations 期刊论文
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 2021, 卷号: 386, 页码: 20
作者:  Yan, Liang;  Zhou, Tao
收藏  |  浏览/下载：103/0  |  提交时间：2022/04/02
Stein variational gradient decent  Bayesian inference  Deep learning  Local approximation  
Optimal design for kernel interpolation: Applications to uncertainty quantification 期刊论文
JOURNAL OF COMPUTATIONAL PHYSICS, 2021, 卷号: 430, 页码: 19
作者:  Narayan, Akil;  Yan, Liang;  Zhou, Tao
收藏  |  浏览/下载：139/0  |  提交时间：2021/04/26
Kernel interpolation  Fekete points  Cholesky decomposition with pivoting  Hermite interpolation  Uncertainty quantification  
AN ACCELERATION STRATEGY FOR RANDOMIZE-THEN-OPTIMIZE SAMPLING VIA DEEP NEURAL NETWORKS* 期刊论文
JOURNAL OF COMPUTATIONAL MATHEMATICS, 2021, 卷号: 39, 期号: 6, 页码: 848-864
作者:  Yan, Liang;  Zhou, Tao
收藏  |  浏览/下载：124/0  |  提交时间：2022/04/02
Bayesian inverse problems  Deep neural network  Markov chain Monte Carlo  
An Adaptive Surrogate Modeling Based on Deep Neural Networks for Large-Scale Bayesian Inverse Problems 期刊论文
COMMUNICATIONS IN COMPUTATIONAL PHYSICS, 2020, 卷号: 28, 期号: 5, 页码: 2180-2205
作者:  Yan, Liang;  Zhou, Tao
收藏  |  浏览/下载：134/0  |  提交时间：2021/01/14
Bayesian inverse problems  deep neural networks  multi-fidelity surrogate modeling  Markov chain Monte Carlo  
Adaptive multi-fidelity polynomial chaos approach to Bayesian inference in inverse problems 期刊论文
JOURNAL OF COMPUTATIONAL PHYSICS, 2019, 卷号: 381, 页码: 110-128
作者:  Yan, Liang;  Zhou, Tao
收藏  |  浏览/下载：169/0  |  提交时间：2019/03/11
Bayesian inverse problems  Multi-fidelity polynomial chaos  Surrogate modeling  Markov chain Monte Carlo  
AN ADAPTIVE MULTIFIDELITY PC-BASED ENSEMBLE KALMAN INVERSION FOR INVERSE PROBLEMS 期刊论文
INTERNATIONAL JOURNAL FOR UNCERTAINTY QUANTIFICATION, 2019, 卷号: 9, 期号: 3, 页码: 205-220
作者:  Yan, Liang;  Zhou, Tao
收藏  |  浏览/下载：158/0  |  提交时间：2020/01/10
Bayesian inverse problems  ensemble Kalman inversion  multifidelity polynomial chaos  surrogate modeling