首页|University of Basel Reports Findings in Machine Learning (Systematic improvement of empirical energy functions in the era of machine learning)
University of Basel Reports Findings in Machine Learning (Systematic improvement of empirical energy functions in the era of machine learning)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning is th e subject of a report. According to news originating from Basel, Switzerland, by NewsRx correspondents, research stated, “The impact of targeted replacement of individual terms in empirical force fields is quantitatively assessed for pure w ater, dichloromethane (CH Cl ), and solvated K and Cl ions. For the electrostati c interactions, point charges (PCs) and machine learning (ML)-based minimally di stributed charges (MDCM) fitted to the molecular electrostatic potential are eva luated together with electrostatics based on the Coulomb integral.”
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