首页|Investigators from Princeton University Zero in on Machine Learning (Weak Baseli nes and Reporting Biases Lead To Overoptimism In Machine Learning for Fluid-rela ted Partial Differential Equations)
Investigators from Princeton University Zero in on Machine Learning (Weak Baseli nes and Reporting Biases Lead To Overoptimism In Machine Learning for Fluid-rela ted Partial Differential Equations)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – New research on Machine Learning is the subject o f a report. According to news originating from Princeton, New Jersey, by NewsRx correspondents, research stated, “One of the most promising applications of mach ine learning in computational physics is to accelerate the solution of partial d ifferential equations (PDEs). The key objective of machine-learning-based PDE so lvers is to output a sufficiently accurate solution faster than standard numeric al methods, which are used as a baseline comparison.”
PrincetonNew JerseyUnited StatesNo rth and Central AmericaCyborgsEmerging TechnologiesMachine LearningPrinc eton University
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