Robotics & Machine Learning Daily News2024,Issue(Jan.5) :2-2.

Brigham Young University Reports Findings in Machine Learning (TrIP Transformer Interatomic Potential Predicts Realistic Energy Surface Using Physical Bias)

Robotics & Machine Learning Daily News2024,Issue(Jan.5) :2-2.

Brigham Young University Reports Findings in Machine Learning (TrIP Transformer Interatomic Potential Predicts Realistic Energy Surface Using Physical Bias)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews – New research on Machine Learning is the subject of a report. According to news reportingoriginating in Provo, Utah, by NewsRx journalists, research stated, “Accurate interatomic energies andforces enable high-quality molecular dynamics simulations, torsion scans, potential energy surface mappings,and geometry optimizations. Machine learning algorithms have enabled rapid estimates of the energies andforces with high accuracy.”

Key words

Provo/Utah/United States/North and Central America/Cyborgs/Emerging Technologies/Machine Learning/Molecular Dynamics/Physics

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
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