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Interpretable machine learning methods applied to jet background subtraction in heavy-ion collisions

An Engineering Model for Static Yawed Wind Turbines Based on Actuator Line Simulations and Symbolic Regression

Застосування моделей машинного навчання для ефективної оцінки рухливості носіїв у кремнії

Jet quenching identification via supervised learning in simulated heavy-ion collisions

Deep learning approach for predicting multiple observables in Au+Au collisions at energies available at the BNL Relativistic Heavy Ion Collider

Jet momentum reconstruction in the QGP background with machine learning

Reconstructing jet azimuthal anisotropies with cumulants

Machine learning for the analysis of hard probes

SymbolFit: Automatic Parametric Modeling with Symbolic Regression

Accelerating graph-based tracking tasks with symbolic regression

Boosted top tagging and its interpretation using Shapley values

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