首页|Study Data from Texas A&M University Provide New Insights into Mach ine Learning (Adaptive Loss Weighting for Machine Learning Interatomic Potential s)
Study Data from Texas A&M University Provide New Insights into Mach ine Learning (Adaptive Loss Weighting for Machine Learning Interatomic Potential s)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators discuss new findings in Machine Learning. According to news originatingfrom College Station, Texas, by NewsRx correspondents, research stated, “Training machine learninginteratomic p otentials often requires optimizing a loss function composed of three variables: potentialenergies, forces, and stress. The contribution of each variable to th e total loss is typically weighted usingfixed coefficients.”
College StationTexasUnited StatesN orth and Central AmericaCyborgsEmerging TechnologiesMachine LearningTexa s A&M University
NETL
NSTL
