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.
Total project length: 175/350 hours.
Application of optimal transport techniques using deep learning for classification, anomaly detection and graph generative models in high energy physics.
Strong machine learning skills, good knowledge of C++ and Python. Interest in Machine Learning algorithms and applications.
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.