Machine Learning

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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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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Machine Learning Pipelines with Modern Big Data Tools for High Energy Physics
The effective utilization at scale of complex machine learning (ML) techniques for HEP use cases poses several technological …
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