NeuroBayes
The NeuroBayes neural network package. Detailed analysis of correlated data plays a vital role in modern analyses. We present a sophisticated neural network package based on Bayesian statistics which can be used for both classification and event-by-event prediction of the complete probability density distribution for continuous quantities. The network provides numerous possibilities to automatically preprocess the input variables and uses advanced regularisation and pruning techniques to essentially eliminate the risk of overtraining. Examples from physics and industry are given.
Keywords for this software
References in zbMATH (referenced in 2 articles )
Showing results 1 to 2 of 2.
Sorted by year (- Wick, Felix; Kerzel, Ulrich; Hahn, Martin; Wolf, Moritz; Singhal, Trapti; Stemmer, Daniel; Ernst, Jakob; Feindt, Michael: Demand forecasting of individual probability density functions with machine learning (2021)
- Sean Benson; Konstantin Gizdov: HEPDrone: a toolkit for the mass application of machine learning in High Energy Physics (2017) arXiv