Extracting the Chiral Contribution to the Negative Longitudinal Magnetoresistance in Epitaxial Pr 2 Ir 2 O 7 Thin Films
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Regularized or Bayesian inversion has revolutionized our ability to reconstruct images from incomplete data.
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Natural Language Processing (NLP) is a branch of Artificial Intelligence (AI) concerned with solving language tasks by modeling large amounts of textual data. Some NLP techniques use word embeddings which are semantic models where machine learning (ML) is used to learn to cluster semantically related words by learning about word co-occurrences in the original training text. Unfortunately, these models tend to reflect or even exaggerate biases that are present in the training corpus. Here we describe the Word Embedding Navigator (WEN), which is a tool for exploring word embedding models. We examine a specific potential use case for this tool: interactive discovery and neutralization of gender bias in word embedding models, and compare this human-in-the-loop approach to reducing bias in word embeddings with a debiasing post-processing technique.
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Libraries around the world use Springshare library products to expand their reference and information literacy services. The scholarly literature primarily addresses the use of Springshare’s LibGuides and LibChat in academic libraries. During the COVID-19 pandemic, virtual reference became the norm at all types of libraries, many turning to new tools to serve their patrons. This article describes the implementation and marketing of LibGuides and LibChat applications at the Los Alamos National Laboratory Research Library at the Los Alamos National Laboratory (LANL). These Springshare tools helped the LANL Research Library close service gaps during the COVID-19 work from home initiative at LANL.
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