...Tomas Slimak; Andreas Zwölfer; Bojidar Todorov; Daniel J. Rixen Artificial neural networks (NNs) are a type of machine learning (ML) algorithm that mimics the functioning of the human brain to learn and generalize patterns from large amounts of data without the need for explicit knowledge...

... this problem, in this paper, a physics-guided machine learning (ML) method for prediction of peak impact forces, within predefined modification dimensions of collaborative applications, is proposed. Along with a pose-dependent linearized model, an ensemble of boosted decision tree (BDT) in combination...

... problem, and a stability analysis is performed to study the governing bifurcations. In addition, we build a machine learning framework where neural net (NN) simulators are trained to predict the performance measures of the gated waveguide in terms of certain transmissibility and nonreciprocity measures...