首页|Researchers from University of Stuttgart Detail New Studies and Findings in the Area of Machine Learning (Scientific Deep Machine Learning Concepts for the Pred iction of Concentration Profiles and Chemical Reaction Kinetics: Consideration of ...)
Researchers from University of Stuttgart Detail New Studies and Findings in the Area of Machine Learning (Scientific Deep Machine Learning Concepts for the Pred iction of Concentration Profiles and Chemical Reaction Kinetics: Consideration of ...)
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 – A new study on Machine Learning is now available. According to news originating from Stuttgart, Germany, by NewsRx cor respondents, research stated, “Emerging concepts from scientific deep machine le arning such as physics-informed neural networks (PINNs) enable a data-driven app roach for the study of complex kinetic problems. We present an extended framewor k that combines the advantages of PINNs with the detailed consideration of exper imental parameter variations for the simulation and prediction of chemical react ion kinetics.”
StuttgartGermanyEuropeCyborgsEme rging TechnologiesMachine LearningUniversity of Stuttgart
NETL
NSTL
