Robotics & Machine Learning Daily News2024,Issue(Jan.3) :44-44.

New Findings in Machine Learning Described from Johns Hopkins University (Physics-agnostic and Physics-infused Machine Learning for Thin Films Flows: Modelling, and Predictions From Small Data)

Robotics & Machine Learning Daily News2024,Issue(Jan.3) :44-44.

New Findings in Machine Learning Described from Johns Hopkins University (Physics-agnostic and Physics-infused Machine Learning for Thin Films Flows: Modelling, and Predictions From Small Data)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Fresh data on Machine Learning are presented in a new report. According to newsreporting from Baltimore, Maryland, by NewsRx journalists, research stated, “Numerical simulations ofmultiphase flows are crucial in numerous engineering applications, but are often limited by the computationallydemanding solution of the Navier-Stokes (NS) equations. The development of surrogate modelsrelies on involved algebra and several assumptions.”

Key words

Baltimore/Maryland/United States/North and Central America/Cyborgs/Emerging Technologies/Machine Learning/Johns Hopkins University

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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