Speaker
Peter Fackeldey
(Princeton University (US))
Description
The propagation of gradients with backpropagation through a HEP analysis for end-to-end optimization begins at the last step of a physics analysis: the statistical measurement. Therefore, it is crucial to have statistical tools that are fully differentiable in order to calculate gradients with respect to the final physical measurement. This contribution provides an overview of how such fully differentiable statistical tools can be achieved with the JAX ecosystem.