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Trees and Forests in Nuclear Physics

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arxiv 2002.10290 v2 pith:P5N5T3WO submitted 2020-02-24 nucl-th cs.LGnucl-ex

classification nucl-thcs.LGnucl-ex
keywords nucleardecisionmodelphysicstreetreesaccuracyalgorithm
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We present a simple introduction to the decision tree algorithm using some examples from nuclear physics. We show how to improve the accuracy of the classical liquid drop nuclear mass model by performing Feature Engineering with a decision tree. Finally, we apply the method to the Duflo-Zuker model showing that, despite their simplicity, decision trees are capable of improving the description of nuclear masses using a limited number of free parameters.

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  1. TELLER: Non-intrusive Cross-Layer Root-Cause Analysis for LLM Inference

    cs.SE 2026-08 conditional novelty 6.0 of 10

    TELLER reconstructs per-request call-chain trees from traces and logs, compresses them with a structure-preserving tokenizer, and achieves strong root-cause localization for LLM inference failures.

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