Neural Networks

Learning new physics efficiently with nonparametric methods
We present a machine learning approach for model-independent new physics searches. The corresponding algorithm is powered by recent …
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Beyond Transformers: fault type detection in maintenance tickets with Kernel Methods, Boost Decision Trees and Neural Networks
The proper handling of customer tickets and main-tenance requests is pivotal for enterprises as it directly impacts customer …
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Learning new physics from an imperfect machine
We show how to deal with uncertainties on the Standard Model predictions in an agnostic new physics search strategy that exploits …
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Learning multivariate new physics
We discuss a method that employs a multilayer perceptron to detect deviations from a reference model in large multivariate datasets. …
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