Litcius/Paper detail

Predicting <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si1.svg"><mml:mrow><mml:mo stretchy="true">(</mml:mo><mml:mrow><mml:mi mathvariant="bold-italic">n</mml:mi><mml:mo>,</mml:mo><mml:mn mathvariant="bold">3</mml:mn><mml:mi mathvariant="bold-italic">n</mml:mi></mml:mrow><mml:mo stretchy="true">)</mml:mo></mml:mrow></mml:math> nuclear reaction cross-sections using XGBoost and Leave-One-Out Cross-Validation

Yiğit Ali Üncü, Taner Danışman, Hasan Özdoğan

2025Applied Radiation and Isotopes11 citationsDOI

Topics & Concepts

Cross-validationNuclear physicsComputer sciencePhysicsArtificial intelligenceNuclear reactor physics and engineeringNuclear Physics and ApplicationsAdvanced X-ray and CT Imaging
Predicting <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si1.svg"><mml:mrow><mml:mo stretchy="true">(</mml:mo><mml:mrow><mml:mi mathvariant="bold-italic">n</mml:mi><mml:mo>,</mml:mo><mml:mn mathvariant="bold">3</mml:mn><mml:mi mathvariant="bold-italic">n</mml:mi></mml:mrow><mml:mo stretchy="true">)</mml:mo></mml:mrow></mml:math> nuclear reaction cross-sections using XGBoost and Leave-One-Out Cross-Validation | Litcius