The NeuroBayes neural network package

By M. Feindt, U. Kerzel. 2006

316 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/484cff376637c668c3f89ab091470b715f79f0c0

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Jean-Roch Vlimant
2. Salvatore Rappoccio
3. Y. Kim
4. S. Thomas
5. Alexander Belyaev
6. Wolfgang Waltenberger
7. Philip C. Harris
8. É. Conte

In Control and Systems Engineering

1. Wolfgang Waltenberger
2. Cms Collaboration
3. Matthew Fisher
4. Simone Paoletti

Citations in the corpus

• The LHCb trigger and its performance in 2011 (2012, methodology): “In order to enrich theBs candidates two dedicated neural networks based on the NeuroBayes neura l network package [10] are used.”
• Measurement of the single-top-quark t-channel cross section in pp collisions at $ \sqrt{s}=7 $ TeV (2012, methodology): “The NeuroBayes package [26, 27] used for this NN analysis combines a three-layer feedforward NN with a complex, but robust, preprocessing.”
• Test of lepton universality with B0 → K*0ℓ+ℓ− decays (2017, unknown): “The separation of the signal from the combinatorial background is based on neuralnetwork classifiers [50].”