Evaluating 239Pu(n,f) cross sections via machine learning using experimental data, covariances, and measurement features

Research article (Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment, 2020) · cited 15× · AI/ML
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Evaluating 239Pu(n,f) cross sections via machine learning using experimental data, covariances, and measurement features

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Evaluating 239Pu(n,f) cross sections via machine learning using experimental data, covariances, and measurement features is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). Evaluating 239Pu(n,f) cross sections via machine learning using experimental data, covariances, and measurement features. Retrieved May 24, 2026, from https://4ort.xyz/entity/evaluating-239pu-n-f-cross-sections-via-machine-learning-using-experimental-data-covariances-and-measurement-features
MLA “Evaluating 239Pu(n,f) cross sections via machine learning using experimental data, covariances, and measurement features.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/evaluating-239pu-n-f-cross-sections-via-machine-learning-using-experimental-data-covariances-and-measurement-features.
BibTeX @misc{4ortxyz_evaluating-239pu-n-f-cross-sections-via-machine-learning-using-experimental-data-covariances-and-measurement-features_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Evaluating 239Pu(n,f) cross sections via machine learning using experimental data, covariances, and measurement features}}, year = {2026}, url = {https://4ort.xyz/entity/evaluating-239pu-n-f-cross-sections-via-machine-learning-using-experimental-data-covariances-and-measurement-features}, note = {Accessed: 2026-05-24}}
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