2 citations · 2 across the 5 of their papers we have counts for
6 papers
Domain Adaptation against Background Sculpting in Anomaly Detection at the LHC
Vincent Benne, Marie Hein, Michael Krämer +3
Weakly supervised anomaly detection has been shown to be an effective tool for model-agnostic searches for new physics, especially in the context of resonance searches. However, co…
Kitchen Sink Anomaly Detection
Ranit Das, Marie Hein, Gregor Kasieczka +6
An enormous amount of R&D effort has resulted in many new resonant anomaly detection methods being proposed in recent years. However, the vast majority of previous R&D studies have…
Look everywhere effects in anomaly detection
Marie Hein, Benjamin Nachman, David Shih
Machine learning-based anomaly detection methods are able to search high-dimensional spaces for hints of new physics with much less theory bias than traditional searches. However,…
How to pick the best anomaly detector?
Marie Hein, Gregor Kasieczka, Michael Krämer +3
Anomaly detection has the potential to discover new physics in unexplored regions of the data. However, choosing the best anomaly detector for a given data set in a model-agnostic…
Accurate and robust methods for direct background estimation in resonant anomaly detection
Ranit Das, Thorben Finke, Marie Hein +4
Resonant anomaly detection methods have great potential for enhancing the sensitivity of traditional bump hunt searches. A key component of these methods is a high quality backgrou…
Back To The Roots: Tree-Based Algorithms for Weakly Supervised Anomaly Detection
Thorben Finke, Marie Hein, Gregor Kasieczka +6
Weakly supervised methods have emerged as a powerful tool for model-agnostic anomaly detection at the Large Hadron Collider (LHC). While these methods have shown remarkable perform…