首页|Report Summarizes Machine Learning Study Findings from Xiamen University (Tell M achine Learning Potentials What They Are Needed For: Simulation-oriented Trainin g Exemplified for Glycine)
Report Summarizes Machine Learning Study Findings from Xiamen University (Tell M achine Learning Potentials What They Are Needed For: Simulation-oriented Trainin g Exemplified for Glycine)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News - Current study results on Machine Learn ing have been published. According to news reporting out of Fujian, People’s Rep ublic of China, by NewsRx editors, research stated, “Machine learning potentials (MLPs) are widely applied as an efficient alternative way to represent potentia l energy surfaces (PESs) in many chemical simulations. The MLPs are often evalua ted with the root-mean-square errors on the test set drawn from the same distrib ution as the training data.”
FujianPeople’s Republic of ChinaAsiaAmino AcidsCyborgsEmerging TechnologiesGlycineMachine LearningXiamen University
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