Large Scale Data Analysis - Scientific Visualization: Uncertainty, Multifield, Biomedical, and Scalable Visualization - page 332

cal distributions obtained from conditional feature sets to be easily related back to
the sets of features contributing to the statistic through feature-based visualization
and linked views.
Acknowledgments This research used resources of the Oak Ridge Leadership Computing Facility
at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S.
Department of Energy under Contract No.DE-AC05-00OR22725. This research used resources
of the National Energy Research Scientific Computing Center, which is supported by the Office
of Science of the U.S. Department of Energy under Contract No.DE-AC02-05CH11231. Sandia
National Laboratories is a multiprogram laboratory managed and operated by Sandia Corporation,
a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's
National Nuclear Security Administration under contract DE-AC04-94AL85000. This work was
performed under the auspices of the U.S.Department of Energy by Lawrence Livermore National
Laboratory under Contract DE-AC52- 07NA27344. This work is supported in part by BNSF CISE
ACI-0904631, NSG IIS- 1045032,NSF EFT ACI-0906379,DOE/NEUP 120341, DOE/Codesign
P01180734,DOE/SciDAC DESC0007446, and CCMSC DE-NA0002375.
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