14 citations · 14 across the 3 of their papers we have counts for
3 papers
Quasiprobabilistic Density Ratio Estimation with a Reverse Engineered Classification Loss Function
Matthew Drnevich, Stephen Jiggins, Kyle Cranmer
We consider a generalization of the classifier-based density-ratio estimation task to a quasiprobabilistic setting where probability densities can be negative. The problem with mos…
Neural Quasiprobabilistic Likelihood Ratio Estimation with Negatively Weighted Data
Matthew Drnevich, Stephen Jiggins, Judith Katzy +1
Motivated by real-world situations found in high energy particle physics, we consider a generalisation of the likelihood-ratio estimation task to a quasiprobabilistic setting where…
Reframing Jet Physics with New Computational Methods
Kyle Cranmer, Matthew Drnevich, Sebastian Macaluso +1
We reframe common tasks in jet physics in probabilistic terms, including jet reconstruction, Monte Carlo tuning, matrix element - parton shower matching for large jet multiplicity,…