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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：102/0  |  提交时间：2022/04/02
Stein variational gradient decent  Bayesian inference  Deep learning  Local approximation  
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：123/0  |  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：131/0  |  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：166/0  |  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：156/0  |  提交时间：2020/01/10
Bayesian inverse problems  ensemble Kalman inversion  multifidelity polynomial chaos  surrogate modeling  
On input design for regularized LTI system identification: Power-constrained input 期刊论文
AUTOMATICA, 2018, 卷号: 97, 页码: 327-338
作者:  Mu, Biqiang;  Chen, Tianshi
收藏  |  浏览/下载：280/0  |  提交时间：2018/11/16
Input design  Bayesian mean square error  Kernel-based regularization  LTI system identification  Convex optimization