首页|Investigators from University of Glasgow Zero in on Machine Learning (Boundary C onstrained Gaussian Processes for Robust Physicsinformed Machine Learning of Li near Partial Differential Equations)
Investigators from University of Glasgow Zero in on Machine Learning (Boundary C onstrained Gaussian Processes for Robust Physicsinformed Machine Learning of Li near Partial Differential Equations)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Data detailed on Machine Learning have been presented. According to news reportingfrom Glasgow, United Kingdom, by Ne wsRx journalists, research stated, “We introduce a framework fordesigning bound ary constrained Gaussian process (BCGP) priors for exact enforcement of linear b oundaryconditions, and apply it to the machine learning of (initial) boundary v alue problems involving linearpartial differential equations (PDEs). In contras t to existing work, we illustrate how to design boundaryconstrained mean and ke rnel functions for all classes of boundary conditions typically used in PDE modelling, namely Dirichlet, Neumann, Robin and mixed conditions.”
GlasgowUnited KingdomEuropeCyborgsEmerging TechnologiesGaussian ProcessesMachine LearningUniversity of Gla sgow
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