16-18 October 2023
Campus Unteres Schloss | University of Siegen
Europe/Berlin timezone

Back to the Roots: Tree-Based Algorithms for Weakly Supervised Anomaly Detection

18 Oct 2023, 13:30
Seminarzentrum (Campus Unteres Schloss | University of Siegen)


Campus Unteres Schloss | University of Siegen

Obergraben 25 57072 Siegen


Marie Hein (RWTH Aachen University)


Weakly supervised methods have emerged as a powerful tool for model agnostic anomaly detection at the LHC. While these methods have shown remarkable performance on specific signatures such as di-jet resonances, their application in a more model-agnostic manner requires dealing with a larger number of potentially noisy input features. We show that neural networks struggle with noisy input features and that this issue can be solved by using boosted decision trees. Overall, boosted decision trees have a superior performance in the weakly supervised setting than neural networks. Additionally, we significantly improve the performance by using an extended set of features.

Primary authors

Thorben Finke (RWTH Aachen University) Marie Hein (RWTH Aachen University) Gregor Kasieczka (Universität Hamburg) Michael Krämer (RWTH Aachen University) Alexander Mück (RWTH Aachen University) Parada Prangchaikul (Universität Hamburg) Tobias Quadfasel (Universität Hamburg) David Shih (Rutgers University) Manuel Sommerhalder (Universität Hamburg)

Presentation Materials

Your browser is out of date!

Update your browser to view this website correctly. Update my browser now