Between the years 2015 and 2019, members of the Horizon 2020-funded Innovative Training Network named “AMVA4NewPhysics” studied the customization and application of advanced multivariate analysis methods and statistical learning tools to high-energy physics problems, as well as developed entirely new ones. Many of those methods were successfully used to improve the sensitivity of data analyses performed by the ATLAS and CMS experiments at the CERN Large Hadron Collider; several others, still in the testing phase, promise to further improve the precision of measurements of fundamental physics parameters and the reach of searches for new phenomena. In this paper, the most relevant new tools, among those studied and developed, are presented al...
We describe the outcome of a data challenge conducted as part of the Dark Machines Initiative and th...
In this thesis we have searched for new physics phenomena predicted by Supersymmetry and Dark Matter...
The lectures will cover multivariate statistical methods and their applications in High Energy Physi...
International audienceBetween the years 2015 and 2019, members of the Horizon 2020-funded Innovative...
Machine learning entails a broad range of techniques that have been widely used in Science and Engin...
This project focuses on testing and developing algorithms for multivariate data analysis, that separ...
Compelling experimental evidence suggests the existence of new physics beyond the well-established a...
Machine learning techniques have been used extensively in several domains of Science and Engineering...
The Large Hadron Collider, located at the CERN laboratories in Geneva, is the largest particle accel...
This paper describes a strategy for a general search used by the ATLAS Collaboration to find potenti...
We discuss a method that employs a multilayer perceptron to detect deviations from a reference model...
Because the emphasis of the LHC is on 5 sigma discoveries and the LHC environment induces high syste...
The lectures will cover multivariate statistical methods and their applications in High Energy Physi...
In high energy particle physics, machine learning has already proven to be an indispensable techniqu...
The use of machine learning is increasing at the LHC experiments including both the ATLAS and LHCb c...
We describe the outcome of a data challenge conducted as part of the Dark Machines Initiative and th...
In this thesis we have searched for new physics phenomena predicted by Supersymmetry and Dark Matter...
The lectures will cover multivariate statistical methods and their applications in High Energy Physi...
International audienceBetween the years 2015 and 2019, members of the Horizon 2020-funded Innovative...
Machine learning entails a broad range of techniques that have been widely used in Science and Engin...
This project focuses on testing and developing algorithms for multivariate data analysis, that separ...
Compelling experimental evidence suggests the existence of new physics beyond the well-established a...
Machine learning techniques have been used extensively in several domains of Science and Engineering...
The Large Hadron Collider, located at the CERN laboratories in Geneva, is the largest particle accel...
This paper describes a strategy for a general search used by the ATLAS Collaboration to find potenti...
We discuss a method that employs a multilayer perceptron to detect deviations from a reference model...
Because the emphasis of the LHC is on 5 sigma discoveries and the LHC environment induces high syste...
The lectures will cover multivariate statistical methods and their applications in High Energy Physi...
In high energy particle physics, machine learning has already proven to be an indispensable techniqu...
The use of machine learning is increasing at the LHC experiments including both the ATLAS and LHCb c...
We describe the outcome of a data challenge conducted as part of the Dark Machines Initiative and th...
In this thesis we have searched for new physics phenomena predicted by Supersymmetry and Dark Matter...
The lectures will cover multivariate statistical methods and their applications in High Energy Physi...