首页|Investigators at National Polytechnic Institute Detail Findings in Machine Learning (Physics-inspired Evolutionary Machine Learning Method: From the Schrodinger Equation To an Orbital-free-dft Kinetic Energy Functional)
Investigators at National Polytechnic Institute Detail Findings in Machine Learning (Physics-inspired Evolutionary Machine Learning Method: From the Schrodinger Equation To an Orbital-free-dft Kinetic Energy Functional)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators discuss new findings in Machine Learning. According to news reporting from Queretaro, Mexico, by NewsRx journalists, research stated, “We introduce a machine learning (ML)- supervised model function (which is in fact a functional rather than a regular function) that is inspired by the variational principle of physics. This ML hypothesis evolutionary method, termed ML-Omega, allows us to go from data to differential equation(s) underlying the physical (chemical, engineering, etc.) phenomena from which the data are derived from.”
QueretaroMexicoNorth and Central AmericaCyborgsEmerging TechnologiesMachine LearningNational Polytechnic Institute
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