3 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.LG2026
Product units in gated recurrent units improve nuclear-mass prediction
Ziyuan Li, Paulo S. A. Freitas, John W. Clark +1
The prediction of masses of atomic nuclei using machine learning can complement theoretical models and advance the exploration of poorly known domains of the nuclear chart. We prop…
nucl-th2023
Predicting nuclear masses with product-unit networks
Babette Dellen, Uwe Jaekel, Paulo S. A. Freitas +1
Accurate estimation of nuclear masses and their prediction beyond the experimentally explored domains of the nuclear landscape are crucial to an understanding of the fundamental or…
nucl-th2019★ 3 cited
Experiments in machine learning of alpha-decay half-lives
Paulo S. A. Freitas, John W. Clark
Artificial neural networks are trained by a standard backpropagation learning algorithm with regularization to model and predict the systematics of -decay of heavy and superheavy n…