Robotics & Machine Learning Daily News2024,Issue(Nov.11) :69-69.

Recent Findings from State Key Laboratory of Rolling and Automation Highlight Re search in Machine Learning (Employing deep learning in non-parametric inverse vi sualization of elastic-plastic mechanisms in dual-phase steels)

轧制与自动化国家重点实验室最近的研究成果突出了机器学习的研究(深度学习在双相钢弹塑性机理非参数反演中的应用)

Robotics & Machine Learning Daily News2024,Issue(Nov.11) :69-69.

Recent Findings from State Key Laboratory of Rolling and Automation Highlight Re search in Machine Learning (Employing deep learning in non-parametric inverse vi sualization of elastic-plastic mechanisms in dual-phase steels)

轧制与自动化国家重点实验室最近的研究成果突出了机器学习的研究(深度学习在双相钢弹塑性机理非参数反演中的应用)

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摘要

由一名新闻记者-机器人与机器学习日报的工作人员新闻编辑每日新闻-关于人工智能的研究结果在一份新的报告中讨论。根据来自轧钢及自动化国家重点实验室的消息“提高机器学习方法在材料预测中的可解释性”研究性质是材料科学中一个关键但复杂的主题。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Research findings on artificial intell igence are discussed in a new report. According tonews originating from the Sta te Key Laboratory of Rolling and Automation by NewsRx correspondents,research s tated, “Enhancing the interpretability of machine learning methods for predictin g materialproperties is a key, yet complex topic in materials science.”

Key words

State Key Laboratory of Rolling and Auto mation/Cyborgs/Emerging Technologies/Machine Learning

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
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