ZANETTI M.

In biomechanics, a still unresolved question is how to estimate with enough accuracy the volume and mass of each body segment of a subject. This is important for several applications ranging from the rehabilitation of injured subjects to the study of athletic performances via the analysis of the dynamic inertia of each body segment. However,...

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We present a machine learning approach for model-independent new physics searches. The corresponding algorithm is powered by recent large-scale implementations of kernel methods, nonparametric learning algorithms that can approximate any continuous function given enough data. Based on the original proposal by D'Agnolo and Wulzer (Phys Rev D...

We propose an accurate and efficient machine learning approach for monitoring particle detectors in real-time. The goal is to assess the compatibility of incoming experimental data with a reference dataset, characterising the data behaviour under normal circumstances, via a likelihood-ratio hypothesis test. The model is based on a modern...