3 Works

Software examples for the ATLAS Higgs Learning Challenge 2014

Sebastien Binet, Balazs Kegl & David Rousseau
This software package contains several helper scripts that demonstrate event filtering and AMS score evaluation techniques on the ATLAS Higgs Challenge data set.

Learning to discover: the Higgs boson machine learning challenge - Documentation

Claire Adam-Bourdarios, Glen Cowan, Cecile Germain, Isabelle Guyon, Balazs Kegl & David Rousseau
A documentation for the Challenge is provided, with just the sufficient level of explanation for people without any background in physics, nor machine learning.

Dataset from the ATLAS Higgs Boson Machine Learning Challenge 2014

The dataset has been built from official ATLAS full detector simulation, with Higgs to tautau events mixed with different backgrounds. The simulator has two parts. In the first, random proton-proton collisions are simulated based on the knowledge that we have accumulated on particle physics. It reproduces the random microscopic explosions resulting from the proton-proton collisions. In the second part, the resulting particles are tracked through a virtual model of the detector. The process yields simulated...

Registration Year

  • 2015

Resource Types

  • Dataset
  • Software
  • Text