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ISSN 印刷: 2152-5080
ISSN オンライン: 2152-5099
 | Archive FilesSPECIAL ISSUE: CELEBRATING THE ESTABLISHMENT OF A NEW UQ SOCIETY IN CHINA PART 2GUEST EDITOR: TAO ZHOU
 
 DOI: 10.1615/Int.J.UncertaintyQuantification.v9.i3 Table of Contents: 
PREFACE: A SPECIAL ISSUE CELEBRATING A NEW UQ ACTIVITY GROUP IN CHINA
Tao Zhou
v
Tao ZhouLSEC, Institute of Computational Mathematics and Scientific/Engineering Computing,
Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190,
China
 
  ページ
DOI:  10.1615/Int.J.UncertaintyQuantification.v9.i3.10
 
AN ADAPTIVE MULTIFIDELITY PC-BASED ENSEMBLE KALMAN INVERSION FOR INVERSE PROBLEMS
Liang  Yan, Tao Zhou
205-220
Liang  YanDepartment of Mathematics, Southeast University, Nanjing, 210096, China
 
 
Tao ZhouLSEC, Institute of Computational Mathematics and Scientific/Engineering Computing,
Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190,
China
 
  ページ
DOI:  10.1615/Int.J.UncertaintyQuantification.2019029059
 
A GENERAL FRAMEWORK FOR ENHANCING SPARSITY OF GENERALIZED POLYNOMIAL CHAOS EXPANSIONS
Xiu Yang, Xiaoliang Wan, Lin Lin, Huan  Lei
221-243
Xiu YangLehigh University
 
 
Xiaoliang WanDepartment of Mathematics and Center of Computation and Technology, Louisiana State
University, Baton Rouge, LA, 70803
 
 
Lin LinDepartment of Mathematics, University of California, Berkeley and Computational Research
Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720
 
 
Huan  LeiAdvanced Computing, Mathematics and Data Division, Pacific Northwest National
Laboratory, Richland, WA, 99352
 
  ページ
DOI:  10.1615/Int.J.UncertaintyQuantification.2019027864
 
VARIABLE-SEPARATION BASED ITERATIVE ENSEMBLE SMOOTHER FOR BAYESIAN INVERSE PROBLEMS IN ANOMALOUS DIFFUSION REACTION MODELS
Yuming Ba, Lijian  Jiang , Na  Ou
245-273
Yuming BaCollege of Mathematics and Econometrics, Hunan University 1, Changsha 410082, China
 
 
Lijian  Jiang School of Mathematical Sciences, Tongji University, Shanghai 200092, China
 
 
Na  OuCollege of Mathematics and Econometrics, Hunan University 1, Changsha 410082, China
 
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DOI:  10.1615/Int.J.UncertaintyQuantification.2019028759
 
AN EFFICIENT NUMERICAL METHOD FOR UNCERTAINTY QUANTIFICATION IN CARDIOLOGY MODELS
Xindan  Gao, Wenjun  Ying, Zhiwen  Zhang
275-294
Xindan  GaoSchool of Mathematical Sciences, Shanghai Jiao Tong University, 800 Dongchuan Road,
Minhang, Shanghai, P.R. China, 200240
 
 
Wenjun  YingDepartment of Mathematics, The University of Hong Kong, Pokfulam Road, Hong Kong,
SAR, China
 
 
Zhiwen  ZhangDepartment of Mathematics, The University of Hong Kong, Pokfulam Road, Hong Kong,
SAR, China
 
  ページ
DOI:  10.1615/Int.J.UncertaintyQuantification.2019027857
 
USING PARALLEL MARKOV CHAIN MONTE CARLO TO QUANTIFY UNCERTAINTIES IN GEOTHERMAL RESERVOIR CALIBRATION
Tiangang Cui, C.  Fox, G. K.  Nicholls, M. J.  O'Sullivan
295-310
Tiangang CuiSchool of Mathematical Sciences, Monash University, VIC 3800, Australia
 
 
C.  FoxDepartment of Physics, University of Otago, Dunedin 9016, New Zealand
 
 
G. K.  NichollsDepartment of Statistics, University of Oxford, Oxford, OX1 3LG, United Kingdom
 
 
M. J.  O'SullivanDepartment of Engineering Sciences, The University of Auckland, Auckland 1010, New
Zealand
 
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DOI:  10.1615/Int.J.UncertaintyQuantification.2019029282
 
A WEIGHT-BOUNDED IMPORTANCE SAMPLING METHOD FOR VARIANCE REDUCTION
Tenchao  Yu, Linjun  Lu, Jinglai Li
311-319
Tenchao  YuSchool of Mathematical Sciences and Institute of Natural Sciences, Shanghai Jiao Tong
University, 800 Dongchuan Rd, Shanghai 200240, China
 
 
Linjun  LuSchool of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University,
Shanghai 200240, China
 
 
Jinglai LiSchool of Mathematics, University of Birmingham, Birmingham B15 2TT, United Kingdom
 
  ページ
DOI:  10.1615/Int.J.UncertaintyQuantification.2019029511
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