首页|University of Chemistry and Technology Reports Findings in Machine Learning (Fast and accurate excited states predictions: machine learning and diabatization)
University of Chemistry and Technology Reports Findings in Machine Learning (Fast and accurate excited states predictions: machine learning and diabatization)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – New research on Machine Learning is the subject of a report. According to news reportingout of Prague, Czech Republic, by NewsRx editors, research stated, “The efficiency of machine learningalgorithms for electronically excited states is far behind ground-state applications. One of the underlyingproblems is the insufficient smoothness of the fitted potential energy surfaces and other properties in thevicinity of state crossings and conical intersections, which is a prerequisite for an efficient regression.”
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