most citedApplication Of Support Vector Machines To Global Prediction Of Nuclear Properties

31 citations · 31 across the 2 of their papers we have counts for

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nucl-th2006★ 31 cited

Application Of Support Vector Machines To Global Prediction Of Nuclear Properties

John W. Clark, Haochen Li

Advances in statistical learning theory present the opportunity to develop statistical models of quantum many-body systems exhibiting remarkable predictive power. The potential of…

nucl-th2005

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…