Optimal Transport in High Energy Physics

Description

The concept of Optimal Transport (OT) can be very useful in quantifying a distance metric between probability distributions. This project will focus on applying optimal transport methods to classification, anomaly detection and generative modeling tasks in particle physics.

Duration

Total project length: 175 hours.

Task ideas and expected results

Application of optimal transport techniques using deep learning for classification, anomaly detection and graph generative models in high energy physics.

Test

Please use this link to access the test for this project.

Requirements

Strong machine learning skills, good knowledge of C++ and Python. Interest in Machine Learning algorithms and applications.

Mentors

Please DO NOT contact mentors directly by email. Instead, please email ml4-sci@cern.ch with Project Title and include your CV and test results. The mentors will then get in touch with you.

Corresponding Project

Participating Organizations