198 citations · 383 across the 8 of their papers we have counts for
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hep-ph2021
An Exploration of Learnt Representations of W Jets
Jack H. Collins
I present a Variational Autoencoder (VAE) trained on collider physics data (specifically boosted jets), with reconstruction error given by an approximation to the Earth Movers…
hep-ph2021
Comparing Weak- and Unsupervised Methods for Resonant Anomaly Detection
Jack H. Collins, Pablo Martín-Ramiro, Benjamin Nachman +1
Anomaly detection techniques are growing in importance at the Large Hadron Collider (LHC), motivated by the increasing need to search for new physics in a model-agnostic way. In th…
hep-ph2021
The LHC Olympics 2020: A Community Challenge for Anomaly Detection in High Energy Physics
Gregor Kasieczka, Benjamin Nachman, David Shih +44
A new paradigm for data-driven, model-agnostic new physics searches at colliders is emerging, and aims to leverage recent breakthroughs in anomaly detection and machine learning. I…