Statistical Framework for Uncertainty Quantification in Computational Molecular Modeling
نویسندگان
چکیده
منابع مشابه
Stochastic representations and statistical inverse identification for uncertainty quantification in computational mechanics
The paper deals with the statistical inverse problem for the identification of a nonGaussian tensor-valued random field in high stochastic dimension. Such a random field can represent the parameter of a boundary value problem (BVP). The available experimental data, which correspond to observations, can be partial and limited. A general methodology and some algorithms are presented including som...
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While a wealth of experience in the development of uncertainty quantification methods and software tools exists at present, a cohesive software package utilizing massively parallel computing resources does not. The thrust of the work to be discussed herein is the development of such a toolkit, which has leveraged existing software frameworks (e.g., DAKOTA (Design Analysis Kit for OpTimizAtion))...
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Bargaining with reading habit is no need. Reading is not kind of something sold that you can take or not. It is a thing that will change your life to life better. It is the thing that will give you many things around the world and this universe, in the real world and here after. As what will be given by this uncertainty quantification in computational fluid dynamics, how can you bargain with th...
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ژورنال
عنوان ژورنال: IEEE/ACM Transactions on Computational Biology and Bioinformatics
سال: 2019
ISSN: 1545-5963,1557-9964,2374-0043
DOI: 10.1109/tcbb.2017.2771240