Robotics & Machine Learning Daily News2024,Issue(MAY.20) :41-42.

Studies from University of Toronto Yield New Data on Machine Learning (Efficient First Principles Based Modeling via Machine Learning: From Simple Representatio ns To High Entropy Materials)

Robotics & Machine Learning Daily News2024,Issue(MAY.20) :41-42.

Studies from University of Toronto Yield New Data on Machine Learning (Efficient First Principles Based Modeling via Machine Learning: From Simple Representatio ns To High Entropy Materials)

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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 out of Toronto, Canada, by NewsRx ed itors, research stated, “High-entropy materials (HEMs) have recently emerged as a significant category of materials, offering highly tunable properties. However , the scarcity of HEM data in existing density functional theory (DFT) databases , primarily due to computational expense, hinders the development of effective m odeling strategies for computational materials discovery.”

Key words

Toronto/Canada/North and Central Ameri ca/Cyborgs/Emerging Technologies/Machine Learning/University of Toronto

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
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