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Particle identification with machine learning from incomplete data in the ALICE experiment
We also present the integration of the ML project with the ALICE analysis software, and we discuss domain adaptation, the ML technique needed to transfer the knowledge between simulated and real experimental data.
Machine-learning-based particle identification with missing data
In this work, we propose the first method for PID that can be trained with all of the available data examples, including incomplete ones.
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