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中国科学院数学与系统科学研究院机构知识库
KMS Of Academy of mathematics and systems sciences, CAS
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Zhou Tao [2]
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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
Authors:
Yan, Liang
;
Zhou, Tao
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View/Download:56/0
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Submit date: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
Authors:
Yan, Liang
;
Zhou, Tao
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View/Download:60/0
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Submit date: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
Authors:
Yan, Liang
;
Zhou, Tao
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View/Download:78/0
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Submit date: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
Authors:
Yan, Liang
;
Zhou, Tao
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View/Download:113/0
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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
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Submit date: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
Authors:
Mu, Biqiang
;
Chen, Tianshi
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Submit date:2018/11/16
Input design
Bayesian mean square error
Kernel-based regularization
LTI system identification
Convex optimization