首页|Data from Linkoping University Provide New Insights into Machine Learning (Evalu ating and Improving the Predictive Accuracy of Mixing Enthalpies and Volumes In Disordered Alloys From Universal Pretrained Machine Learning Potentials)
Data from Linkoping University Provide New Insights into Machine Learning (Evalu ating and Improving the Predictive Accuracy of Mixing Enthalpies and Volumes In Disordered Alloys From Universal Pretrained Machine Learning Potentials)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators publish new report on Ma chine Learning. According to news reportingfrom Linkoping, Sweden, by NewsRx jo urnalists, research stated, “The advent of machine learning inmaterials science opens the way for exciting and ambitious simulations of large systems and long timescales with the accuracy of ab initio calculations. Recently, several pretr ained universal machine learned interatomic potentials (UPMLIPs) have been publi shed, i.e., potentials distributed with a single set ofweights trained to targe t systems across a very wide range of chemistries and atomic arrangements.”
LinkopingSwedenEuropeCyborgsEmer ging TechnologiesMachine LearningLinkoping University
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