Continuous Feature Networks: A Novel Method to Process Irregularly and Inconsistently Sampled Data With Position-Dependent Features

2024-04-302024-04-302023-12-30http://hdl.handle.net/123456789/15738Artikel auch zu finden unter: https://www.iariajournals.org/intelligent_systems/engUrheberrechtlich geschützthttps://rightsstatements.org/page/InC/1.0/machine learningneural netscontinuous kernelirregularly sampled datareflection spectroscopy004Continuous Feature Networks: A Novel Method to Process Irregularly and Inconsistently Sampled Data With Position-Dependent FeaturesAufsatzMaschinelles LernenNeuronales NetzDatenReflexionsspektroskopieDatenverarbeitung