Robotics & Machine Learning Daily News2024,Issue(Sep.2) :3-4.

Swiss Federal Institute of Technology Lausanne (EPFL) Reports Findings in Machin e Learning (Expanding density-correlation machine learning representations for a nisotropic coarse-grained particles)

Robotics & Machine Learning Daily News2024,Issue(Sep.2) :3-4.

Swiss Federal Institute of Technology Lausanne (EPFL) Reports Findings in Machin e Learning (Expanding density-correlation machine learning representations for a nisotropic coarse-grained particles)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – New research on Machine Learning is th e subject of a report. According to newsreporting originating from Lausanne, Sw itzerland, by NewsRx correspondents, research stated, “Physicsbased,atom-cente red machine learning (ML) representations have been instrumental to the effectiv eintegration of ML within the atomistic simulation community. Many of these rep resentations build off theidea of atoms as having spherical, or isotropic, inte ractions.”

Key words

Lausanne/Switzerland/Europe/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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