35 citations · 50 across the 6 of their papers we have counts for
3 papers · 1 filter
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…
Transforming the Bootstrap: Using Transformers to Compute Scattering Amplitudes in Planar N = 4 Super Yang-Mills Theory
Tianji Cai, Garrett W. Merz, François Charton +4
We pursue the use of deep learning methods to improve state-of-the-art computations in theoretical high-energy physics. Planar N = 4 Super Yang-Mills theory is a close cousin to th…
Robust Anomaly Detection for Particle Physics Using Multi-Background Representation Learning
Abhijith Gandrakota, Lily Zhang, Aahlad Puli +4
Anomaly, or out-of-distribution, detection is a promising tool for aiding discoveries of new particles or processes in particle physics. In this work, we identify and address two o…