首页|Investigators at University of Montpellier Report Findings in Machine Learning ( Dynamic Heterogeneity At the Experimental Glass Transition Predicted By Transfer able Machine Learning)
Investigators at University of Montpellier Report Findings in Machine Learning ( Dynamic Heterogeneity At the Experimental Glass Transition Predicted By Transfer able Machine Learning)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Researchers detail new data in Machine Learning. According to news originating from Montpellier, France, by NewsRx cor respondents, research stated, “We develop a machine learning model, which predic ts structural relaxation from amorphous supercooled liquid structures. The train ed networks are able to predict dynamic heterogeneity across a broad range of te mperatures and time scales with excellent accuracy and transferability.”
MontpellierFranceEuropeCyborgsEm erging TechnologiesMachine LearningUniversity of Montpellier
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