8 citations · 8 across the 2 of their papers we have counts for
3 papers · 1 filter
Statistical Global Modeling of Beta-Decay Halflives Systematics Using Multilayer Feedforward Neural Networks and Support Vector Machines
N. J. Costiris, E. Mavrommatis, K. A. Gernoth +2
In this work, the beta-decay halflives problem is dealt as a nonlinear optimization problem, which is resolved in the statistical framework of Machine Learning (LM). Continuing pas…
One and two proton separation energies from nuclear mass systematics using neural networks
S. Athanassopoulos, E. Mavrommatis, K. A. Gernoth +1
We deal with the systematics of one and two proton separation energies as predicted by our latest global model for the masses of nuclides developed with the use of neural networks.…
Modeling Nuclear Properties with Support Vector Machines
Haochen Li, J. W. Clark, E. Mavrommatis +2
We have made initial studies of the potential of support vector machines (SVM) for providing statistical models of nuclear systematics with demonstrable predictive power. Using SVM…