摘要
由一名新闻记者兼机器人与机器学习的新闻编辑每日新闻-调查人员发布了关于马学习的新报告。根据NewsRx记者从伦敦联合王国发回的新闻报道，研究表明：“Calabi-Yau四重曲面可以构造成复维加权射影空间中的超曲面，该文利用神经网络从加权系统中学习Calabi-Yau Hodge数。其中梯度显著性和符号回归激发了Lan Dau-Ginzburg模型公式的截断，用这种方式构造的任何维Calabi-Yau C的Hodge数。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on Ma chine Learning. According to news reporting originating from London, United King dom, by NewsRx correspondents, research stated, “Calabi-Yau fourfolds may be con structed as hypersurfaces in weighted projective spaces of complex dimension fiv e defined via weight systems of six weights. In this work, neural networks were implemented to learn the Calabi-Yau Hodge numbers from the weight systems, where gradient saliency and symbolic regression then inspired a truncation of the Lan dau-Ginzburg model formula for the Hodge numbers of any dimensional Calabi-Yau c onstructed in this way.”
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