When dealing with computationally expensive simulation codes or process measurement data, surrogate modeling methods are firmly established as facilitators for design space explor...
Dirk Gorissen, Ivo Couckuyt, Eric Laermans, Tom Dh...
In this paper a novel procedure to select the input nodes in neural network modeling is presented and discussed. The approach is developed in a multiple testing framework and so it...
— Today’s spectral reflection prediction models are able to predict the reflection spectra of printed color images with an accuracy as high as the reproduction variability allo...
We consider the problem of learning Bayesian network models in a non-informative setting, where the only available information is a set of observational data, and no background kn...
Abstract. The accuracy of data classification methods depends considerably on the data representation and on the selected features. In this work, the elastic net model selection i...
Line Harder Clemmensen, David Delgado Gomez, Bjarn...