Data Analysis in High-Energy Physics as a Differentiable Program
Machine learning methods are now ubiquitous in physics, but often target objectives that are one or two steps removed from our physics goals. A prominent example of this is the discrimination between signal and background processes, which doesn’t account for the presence of systematic uncertainties – something crucial for the calculation of quantities such as the discovery significance and upper l