摘要
机器人与机器学习每日新闻的一位新闻记者兼新闻编辑-机器学习的最新研究结果已经发表。根据NewsRx编辑在奥地利维也纳的新闻报道，研究表明，“我们介绍了一种新的微磁能量最小化方法，该方法使用物理信息神经网络来寻找一个磁场构型，该构型在没有任何约束优化框架的情况下最小化吉布斯自由能泛函。将Cayley变换应用于神经网络，以确保模型输出生活在旋转矩阵SO(3的李群上。”这项研究的资助者包括奥地利科学基金(FWF)、维也纳科学集群(VSC)、奥地利科学基金(FWF)。
Abstract
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).
NETL
NSTL