Johannes Erdmann

Learning to bin: differentiable and Bayesian optimization for multi-dimensional discriminants in high-energy physics

Abstract Categorizing events using discriminant observables is central to many high-energy physics analyses. Yet, bin boundaries are often chosen manually. A simple, popular choice in multi-classification tasks is to assign events according to the largest per-class score (“argmax...