Optimal equivariant architectures from the symmetries of matrix-element likelihoods
(2025)
Journal Article
Maître, D., Ngairangbam, V. S., & Spannowsky, M. (2025). Optimal equivariant architectures from the symmetries of matrix-element likelihoods. Machine Learning: Science and Technology, 6(1), Article 015059. https://doi.org/10.1088/2632-2153/adbab1
The Matrix-Element Method (MEM) has long been a cornerstone of data analysis in high-energy physics. It leverages theoretical knowledge of parton-level processes and symmetries to evaluate the likelihood of observed events. In parallel, the advent of... Read More about Optimal equivariant architectures from the symmetries of matrix-element likelihoods.