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Celeste Enhancements Create New Opportunities in Sky Surveys - Computing Sciences News Archive

Berkeley, CA – Celeste, a statistical analysis model designed to enhance one of modern astronomy’s most time-tested tools—sky surveys—has gotten a major upgrade that dramatically scales up the process of cataloging astronomical objects. The Celeste code, developed under Berkeley Lab’s MANTISSA project, implements statistical inference to build a fully generative model to mathematically locate and […]



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Celeste Enhancements Create New Opportunities in Sky Surveys - Computing Sciences News Archive

https://cs.lbl.gov/news-media/news/2016/celeste-enhancements-create-new-opportunities-in-sky-surveys

Berkeley, CA – Celeste, a statistical analysis model designed to enhance one of modern astronomy’s most time-tested tools—sky surveys—has gotten a major upgrade that dramatically scales up the process of cataloging astronomical objects. The Celeste code, developed under Berkeley Lab’s MANTISSA project, implements statistical inference to build a fully generative model to mathematically locate and […]



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https://cs.lbl.gov/news-media/news/2016/celeste-enhancements-create-new-opportunities-in-sky-surveys

Celeste Enhancements Create New Opportunities in Sky Surveys - Computing Sciences News Archive

Berkeley, CA – Celeste, a statistical analysis model designed to enhance one of modern astronomy’s most time-tested tools—sky surveys—has gotten a major upgrade that dramatically scales up the process of cataloging astronomical objects. The Celeste code, developed under Berkeley Lab’s MANTISSA project, implements statistical inference to build a fully generative model to mathematically locate and […]

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      Berkeley, CA – Celeste, a statistical analysis model designed to enhance one of modern astronomy’s most time-tested tools—sky surveys—has gotten a major upgrade that dramatically scales up the process of cataloging astronomical objects. The Celeste code, developed under Berkeley Lab’s MANTISSA project, implements statistical inference to build a fully generative model to mathematically locate and […]
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