10 citations · 17 across the 3 of their papers we have counts for
4 papers
Efficient Learning of Model Weights via Changing Features During Training
Marcell Beregi-Kovács, Ágnes Baran, András Hajdu
In this paper, we propose a machine learning model, which dynamically changes the features during training. Our main motivation is to update the model in a small content during the…
JOZSO, a renewed version of the computer code GAMOW for calculating broad neutron resonances in phenomenological nuclear potentials
A. Baran, Cs. Noszaly, T. Vertse
A renewed version of the computer code GAMOW ~\cite{[Ve82]} is given in which the difficulties in calculating broad neutron resonances are amended. New types of phenomenological ne…
Matching polynomial tails to the cut-off Woods-Saxon potential
A. Baran, T. Vertse
Cutting off the tail of the Woods-Saxon and generalized Woods-Saxon potentials changes the distribution of the poles of the -matrix considerably. Here we modify the tail of the…
Distributions of the -matrix poles in Woods-Saxon and cut-off Woods-Saxon potentials
P. Salamon, Á. Baran, T. Vertse
The positions of the -matrix poles are calculated in generalized Woods-Saxon (GWS) potential and in cut-off generalized Woods-Saxon (CGWS) potential. The solutions of the…