Particle/Astro-Machine Learning Seminar

Finding the unknown with resonant anomaly detection


Resonant anomaly detection is an emerging class of unsupervised machine learning methods aiming to enhance the sensitivity of beyond-the-standard-model searches in high-energy physics. Contrary to conventional searches, where an explicit new physics signal model is targeted, this data-driven approach can cover a wide range of signals in a single analysis and with relatively minimal assumptions. I will provide an introduction to the concept and discuss a curated set of recent advances and challenges, as well as an ongoing real-world application.


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