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Modern science is heavily reliant on very powerful computers and insights from very large data sets; thus, the drive for an exascale computer, currently scheduled for deployment by Calendar Year 2023…
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Deep learning’s powerful ability to capture rich features, directly from the raw scientific data, makes it an attractive choice for working with complex scientific data sets; however, applying deep…
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The purpose of this project is to further the research and development of tools that NIEHS can use in its research evaluations of the National Toxicology Program’s (NTP’s) effectiveness. This…
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Deep Learning is a sub-field of machine learning that focuses on learning features from data through multiple layers of abstraction. These features are learned with little human domain knowledge…