Scalable Algorithms for Bayesian Inference of Large-Scale Models from Large-Scale Data

被引：0
作者：
Ghattas, Omar [1 ,2 ]
Isaac, Tobin [3 ]
Petra, Noemi [4 ]
Stadler, Georg [5 ]
机构：
[1] Univ Texas Austin, Inst Computat Engn & Sci, Dept Geol Sci, Austin, TX 78712 USA
[2] Univ Texas Austin, Dept Mech Engn, Inst Computat Engn & Sci, Austin, TX 78712 USA
[3] Univ Chicago, Computat Inst, Chicago, IL 60637 USA
[4] Univ Calif Merced, Sch Nat Sci, Merced, CA USA
[5] NYU, Courant Inst Math Sci, New York, NY USA
来源：
HIGH PERFORMANCE COMPUTING FOR COMPUTATIONAL SCIENCE - VECPAR 2016 | 2017年 / 10150卷
关键词：
LINEAR INVERSE PROBLEMS; STOCHASTIC NEWTON MCMC; A-OPTIMAL DESIGN; ICE-SHEET MODEL; MANTLE FLOW; UNCERTAINTY; PARAMETERS; FORESTS; OCTREES;
D O I：
10.1007/978-3-319-61982-8_1
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
引用
收藏
页码：3 / 6
页数：4
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