Robotics & Machine Learning Daily News2024,Issue(Dec.12) :86-86.

University of Vienna Researcher Updates Current Study Findings on Machine Learni ng (Density-based long-range electrostatic descriptors for machine learning forc e fields)

Robotics & Machine Learning Daily News2024,Issue(Dec.12) :86-86.

University of Vienna Researcher Updates Current Study Findings on Machine Learni ng (Density-based long-range electrostatic descriptors for machine learning forc e fields)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Fresh data on artificial intelligence are presented in a new report. According to newsreporting from the University o f Vienna by NewsRx journalists, research stated, “This study presents along-ran ge descriptor for machine learning force fields that maintains translational and rotational symmetry,similar to short-range descriptors while being able to inc orporate long-range electrostatic interactions. Theproposed descriptor is based on an atomic density representation and is structurally similar to classical short-range atom-centered descriptors, making it straightforward to integrate into machine learning schemes.”

Key words

University of Vienna/Cyborgs/Emerging Technologies/Machine Learning

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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