higgs-boson-challenge

Code for the Higgs Boson Machine Learning Challenge organised by CERN & EPFL

A solution to the Higgs boson machine learning challenge

First project of the EPFL Machine Learning course, which aims to solve the Higgs Boson classification problem using various regression techniques. (2018-2019)

Repo supporting arXiv:2002.01427 [physics.data-an]. Using PyTorch to train neural networks for particle physics.

The discovery of Higgs particle was announced on 4th July 2012. In 2013, Nobel Prize was conferred upon two scientists, Francois Englert and Peter Higgs for their contribution towards its discovery. A characteristic property of Higgs Boson is its decay into other particles through different processes. At the ATLAS detector at CERN, very high ene…

Special curriculum project at UiO. Where the aim was to do the Higgs Boson Machine Learning challenge from 2014 using Neural Networks and Quantum Neural Networks

Higgs Boson ML Challenge

Here I present a signal and noise Residual ANN model classificator for particle collisions Delphes sumulations. I explain how to work with .ROOT data files using the Uproot library and how to create such model.

An AICrowd Challenge: Logistic Regression classifier that predicts whether an event's decay signature was the one of a Higgs Boson

Import the Higgs Machine Learning Challenge data (CSV) to MongoDB Instance

Higgs Boson Challenge: a hard classification task achieved without the help of a machine learning library.

Detecting the Higgs Boson particle with TPUs

Rapport de projet en apprentissage statistique MAIN5 2019-2020. Higgs Boson Machine Learning Kaggle Challenge.