A solution to the Higgs boson machine learning challenge
-
Updated
Dec 12, 2019 - HTML
A solution to the Higgs boson machine learning challenge
Code for the Higgs Boson Machine Learning Challenge organised by CERN & EPFL
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]
Higgs Boson ML Challenge
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
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…
Higgs Boson Challenge: a hard classification task achieved without the help of a machine learning library.
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
Rapport de projet en apprentissage statistique MAIN5 2019-2020. Higgs Boson Machine Learning Kaggle Challenge.
Detecting the Higgs Boson particle with TPUs
Add a description, image, and links to the higgs-boson-challenge topic page so that developers can more easily learn about it.
To associate your repository with the higgs-boson-challenge topic, visit your repo's landing page and select "manage topics."