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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
Authors:  Yan, Liang;  Zhou, Tao
Favorite  |  View/Download:10/0  |  Submit date: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
Authors:  Yan, Liang;  Zhou, Tao
Favorite  |  View/Download:6/0  |  Submit date:2020/01/10
Bayesian inverse problems  ensemble Kalman inversion  multifidelity polynomial chaos  surrogate modeling  
WEIGHTED APPROXIMATE FEKETE POINTS: SAMPLING FOR LEAST-SQUARES POLYNOMIAL APPROXIMATION 期刊论文
SIAM JOURNAL ON SCIENTIFIC COMPUTING, 2018, 卷号: 40, 期号: 1, 页码: A366-A387
Authors:  Guo, Ling;  Narayan, Akil;  Yan, Liang;  Zhou, Tao
Favorite  |  View/Download:6/0  |  Submit date:2018/07/30
uncertainty quantification  least-squares approximations  Fekete points  QR decomposition