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A Bayesian Machine Learning Model for Estimating Building Occupancy from Open Source Data

• Authors : Moehl, Jessica [Oak Ridge Associated Univ., Oak Ridge, TN (United States)]

• Source: Natural Hazards; 81; 3

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Using machine learning to identify factors that govern amorphization of irradiated pyrochlores

• Authors : Uberuaga, Blas [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)] (ORCID:0000000169346219)

• Source: Chemistry of Materials; 29; 6

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Machine learning strategies for systems with invariance properties

• Authors : Templeton, Jeremy [Sandia National Lab. (SNL-CA), Livermore, CA (United States)]

• Source: Journal of Computational Physics; 318; C

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Dynamic Modeling of Learning in Emerging Energy Industries: The Example of Advanced Biofuels in the United States: Preprint

• Authors : Peterson, Steven

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Dynamic Modeling of Learning in Emerging Energy Industries: The Example of Advanced Biofuels in the United States; NREL (National Renewable Energy Laboratory)

• Authors : Vimmerstedt, Laura

• Source: Conference: 33rd International Conference of System Dynamics Society, 19-23 July 2015, Cambridge, Massachusetts

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An error reduction algorithm to improve lidar turbulence estimates for wind energy

• Authors : Clifton, Andrew [National Renewable Energy Lab. (NREL), Golden, CO (United States)] (ORCID:0000000196985083)

• Source: Wind Energy Science (Online); 2; 1

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Scalable Regression Tree Learning on Hadoop using OpenPlanet

• Authors : Prasanna, Viktor

• Source: Conference: International Workshop on MapReduce and its Applications, Delft, the Netherlands June 18- 19, 2012

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Deep PDF parsing to extract features for detecting embedded malware.

• Authors : Cross, Jesse [Missouri University of Science and Technology, Rolla, MO]

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