首页|Study Results from University of Vienna in the Area of Machine Learning Reported (Constraint Free Physics-informed Machine Learning for Micromagnetic Energy Min imization)
Study Results from University of Vienna in the Area of Machine Learning Reported (Constraint Free Physics-informed Machine Learning for Micromagnetic Energy Min imization)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on Machine Learn ing have been published. According to news reporting out of Vienna, Austria, by NewsRx editors, research stated, “We introduce a novel method for micromagnetic energy minimization which uses physics -informed neural networks to find a magne tic configuration which minimizes the Gibbs Free energy functional without the n eed of any constraint optimization framework. The Cayley transform is applied to a neural network to assure that the model output lives on the Lie group of rota tion matrices SO(3).” Funders for this research include Austrian Science Fund (FWF), Vienna Scientific Cluster (VSC), Austrian Science Fund (FWF).
ViennaAustriaEuropeCyborgsEmergi ng TechnologiesMachine LearningUniversity of Vienna
NETL
NSTL
