首页|University of Illinois Reports Findings in Machine Learning (Machine Learning a Simple Interpretable Short-Range Potential for Silica)
University of Illinois Reports Findings in Machine Learning (Machine Learning a Simple Interpretable Short-Range Potential for Silica)
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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 Chicago, Illinois, by NewsRx correspondents, research stated, “A wide array of models, spanning from c omputationally expensive ab initio methods to a spectrum of force-field approach es, have been developed and employed to probe silica polymorphs and understand g rowth processes and atomiclevel dynamical transitions in silica. However, the q uest for a model capable of making accurate predictions with high computational efficiency for various silica polymorphs is still ongoing.”
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