4 citations · 4 across the 1 of their papers we have counts for
3 papers
hep-ph2026
Optimizing Cell-Based Negative Weight Mitigation with Optimal Transport
Lauren Hay, Rishabh Jain, Matt LeBlanc +1
As the accuracy of experimental results in high energy physics (HEP) increases, so does the demand for precision Monte Carlo (MC) simulation. Higher-accuracy event generation at ne…
hep-ph2026
Learning the Geometry of Collider Events with Metric-Aware Deep Sets
Lauren Hay, Rishabh Jain, Matt LeBlanc +1
Optimal transport gives structured data a geometry, but exact evaluation is costly in large pairwise analyses that exploit relationships among distances. Learned surrogates are fas…
physics.data-an2020★ 4 cited
Explainable AI for ML jet taggers using expert variables and layerwise relevance propagation
Garvita Agarwal, Lauren Hay, Ia Iashvili +5
A framework is presented to extract and understand decision-making information from a deep neural network (DNN) classifier of jet substructure tagging techniques. The general metho…