首页|Investigators at University of Florida Report Findings in Machine Learning (Anis otropic Physics-regularized Interpretable Machine Learning of Microstructure Evo lution)
Investigators at University of Florida Report Findings in Machine Learning (Anis otropic Physics-regularized Interpretable Machine Learning of Microstructure Evo lution)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Data detailed on Machine Learning have been presented. According to news reporting from Gainesville, Florida, by NewsR x journalists, research stated, “Anisotropic Physics-Regularized Interpretable M achine Learning Microstructure Evolution (APRIMME) is a general-purpose machine learning solution for grain growth simulations. In prior work, PRIMME employed a deep neural network to predict site-specific migration as a function of its nei ghboring sites to model normal, isotropic, grain growth behavior.”
GainesvilleFloridaUnited StatesNor th and Central AmericaCyborgsEmerging TechnologiesMachine LearningUniver sity of Florida
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