2 citations · 2 across the 2 of their papers we have counts for
4 papers
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…
The Fundamental Limit of Jet Tagging
Joep Geuskens, Nishank Gite, Michael Krämer +4
Identifying the origin of high-energy hadronic jets ('jet tagging') has been a critical benchmark problem for machine learning in particle physics. Jets are ubiquitous at colliders…
Cluster Scanning: a novel approach to resonance searches
Ivan Oleksiyuk, John Andrew Raine, Michael Krämer +2
We propose a new model-independent method for new physics searches called Cluster Scanning. It uses the k-means algorithm to perform clustering in the space of low-level event or j…
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…