首页|New Findings from Pennsylvania State University (Penn State) Describe Advances i n Machine Learning (When ancient numerical demons meet physics-informed machine learning: adjoint-based gradients for implicit differentiable modeling)
New Findings from Pennsylvania State University (Penn State) Describe Advances i n Machine Learning (When ancient numerical demons meet physics-informed machine learning: adjoint-based gradients for implicit differentiable modeling)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators discuss new findings in artificial intelligence. According to news reportingfrom University Park, Penns ylvania, by NewsRx journalists, research stated, “Recent advances in differentiable modeling, a genre of physics-informed machine learning that trains neural ne tworks (NNs) together withprocess-based equations, have shown promise in enhanc ing hydrological models’ accuracy, interpretability,and knowledge-discovery pot ential.”
Pennsylvania State University (Penn Stat e)University ParkPennsylvaniaUnited StatesNorth and Central AmericaCyb orgsEmerging TechnologiesMachine Learning
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