429 citations · 1.6k across the 35 of their papers we have counts for
6 papers · 1 filter
Learning new physics efficiently with nonparametric methods
Marco Letizia, Gianvito Losapio, Marco Rando +5
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, n…
Learning New Physics from an Imperfect Machine
Raffaele Tito d'Agnolo, Gaia Grosso, Maurizio Pierini +2
We show how to deal with uncertainties on the Standard Model predictions in an agnostic new physics search strategy that exploits artificial neural networks. Our approach builds di…
Learning Multivariate New Physics
Raffaele Tito D'Agnolo, Gaia Grosso, Maurizio Pierini +2
We discuss a method that employs a multilayer perceptron to detect deviations from a reference model in large multivariate datasets. Our data analysis strategy does not rely on any…
Setting limits on Effective Field Theories: the case of Dark Matter
F. Pobbe, A. Wulzer, M. Zanetti
The usage of Effective Field Theories (EFT) for LHC new physics searches is receiving increasing attention. It is thus important to clarify all the aspects related with the applica…
Fitting the Higgs to Natural SUSY
Raffaele Tito D'Agnolo, Eric Kuflik, Marco Zanetti
We present a fit to the 2012 LHC Higgs data in different supersymmetric frameworks using naturalness as a guiding principle. We consider the MSSM and its D-term and F-term extensio…
LHC HXSWG interim recommendations to explore the coupling structure of a Higgs-like particle
LHC Higgs Cross Section Working Group, A. David, A. Denner +8
This document presents an interim framework in which the coupling structure of a Higgs-like particle can be studied. After discussing different options and approximations, recommen…