Contrasting the widespread application of data science methods and ever increasing volumes of data, human supervision capacities remain limited. Thus, the efficient allocation of limited resources is required, for example by selection of data for inspection, annotation, or processing.In this talk, we study active sampling approaches, which provi...
Creator:
Krempl, Georg (Otto-von-Guericke-Universität Magdeburg)
Created:
2016-09-15
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
We study the effect of the uncertainty of wind power on the angular stability of power systems, including a single-machine, infinite-bus (SMIB) system, and a three-generator, nine-bus multi-machine system, which are subject to a self-clearing three-phase fault. Probability density function (PDF) and Monte Carlo (MC) methods are used to calculate...
Creator:
Tartakovsky, Alexandre (Battelle Pacific Northwest National Laboratory)
Created:
2016-02-22
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
Barth, Timothy J. (NASA Ames Research Center); Ghattas, Omar (The University of Texas at Austin); Jofre, Alejandro Rene (University of Chile); Lipton, Robert P. (Louisiana State University); Robinson, Stephen Michael (University of Wisconsin, Madison)
Created:
2010-10-20
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
Mathematical models are employed ubiquitously for description, prediction and decision making. In addressing end-goal objectives, great care needs to be devoted to attainment of appropriate balance of inexactness throughout the various stages of the end goal process (e.g. modeling and optimization). Disregard to such considerations, either entai...
Creator:
Horesh, Lior (IBM)
Created:
2016-02-22
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
When performing simulations of soft materials such as proteins and polymers, physical properties of interest always have associated statistical uncertainty. This inability to calculate properties exactly and understand the uncertainties precisely is one of the most important factors limiting our understanding how predictive such simulations actu...
Creator:
Shirts, Michael R. (University of Virginia)
Created:
2013-12-16
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
Computational models of complex physical systems are fraught withuncertainties. These include uncertainties in initial or boundaryconditions, uncertainties in model parameters and/or the experimentaldata used to calibrate them and uncertainties arising fromimperfections in the models used in the simulations. Mathematicalmodels of these uncertain...
Creator:
Moser, Robert D. (The University of Texas at Austin)
Created:
2010-10-20
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.