Machine Learning techniques to approximate Matrix Element Method calculations

The Matrix Element Method is a powerful tool for data analysis of High Energy Physics data, and could be especially useful for future analysis of the interesting ttH(b¯b) process. However it is slow and computationally expensive to use, limiting its applicability. This project aims to use machine learning and artificial neural networks to speed up the computation.