NIST · ИТ · 04ded7e27ed3db8ff946
On-the-fly closed-loop materials discovery via Bayesian active learning
Active learning—the field of machine learning (ML) dedicated to optimal experiment design—has played a part in science as far back as the 18th century when Laplace used it to guide his discovery of celestial mechanics. In this work, we focus a closed-loop
NIST · ИТОфициальный источник · 2020-11-24
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"title_en": "On-the-fly closed-loop materials discovery via Bayesian active learning",
"designation": "",
"series": "",
"status": "",
"date": "2020-11-24",
"date_original": "November 24, 2020",
"url": "https://www.nist.gov/publications/fly-closed-loop-materials-discovery-bayesian-active-learning",
"source": "NIST Publications",
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"authors_en": "Aaron Kusne , Heshan Yu, Huairuo Zhang, Jason Hattrick-Simpers , Brian DeCost , Albert Davydov , Leonid A. Bendersky , Apurva Mehta, Ichiro Takeuchi",
"abstract_excerpt_en": "Active learning—the field of machine learning (ML) dedicated to optimal experiment design—has played a part in science as far back as the 18th century when Laplace used it to guide his discovery of celestial mechanics. In this work, we focus a closed-loop",
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{
"title_en": "On-the-fly closed-loop materials discovery via Bayesian active learning",
"designation": "",
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"date": "2020-11-24",
"date_original": "November 24, 2020",
"url": "https://www.nist.gov/publications/fly-closed-loop-materials-discovery-bayesian-active-learning",
"source": "NIST Publications",
"display_en": "",
"authors_en": "Aaron Kusne , Heshan Yu, Huairuo Zhang, Jason Hattrick-Simpers , Brian DeCost , Albert Davydov , Leonid A. Bendersky , Apurva Mehta, Ichiro Takeuchi",
"abstract_excerpt_en": "Active learning—the field of machine learning (ML) dedicated to optimal experiment design—has played a part in science as far back as the 18th century when Laplace used it to guide his discovery of celestial mechanics. In this work, we focus a closed-loop"
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