首页|New Findings from Concordia University Describe Advances in Machine Learning (Su bspace Graph Networks for Real-time Granular Flow Simulation With Applications T o Machine-terrain Interactions)
New Findings from Concordia University Describe Advances in Machine Learning (Su bspace Graph Networks for Real-time Granular Flow Simulation With Applications T o Machine-terrain Interactions)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Researchers detail new data in Machine Learning. According to news reporting fromMontreal, Canada, by NewsRx journali sts, research stated, “Granular flows interacting with rigid bodiesare key to m achine-terrain interactions in robotics and related fields, and still pose sever al open problems.Continuum methods and deep learning, separately and in combina tion, show promise.”
MontrealCanadaNorth and Central Amer icaCyborgsEmerging TechnologiesEngineeringMachine LearningConcordia Un iversity
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