activity
20212026
most citedAutoencoders for unsupervised anomaly detection in high energy physics

99 citations · 126 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2026

Authentication of Copy Detection Patterns via Cross-Camera Dual-Synthetic Referencing

Ivan Oleksiyuk, Roman Chaban, Slava Voloshynovskiy

Copy Detection Patterns (CDPs) are structures printed on physical objects to enable cost-effective authentication. Verification is achieved by comparing a captured image with the d…

hep-ph2025

TRANSIT your events into a new mass: Fast background interpolation for weakly-supervised anomaly searches

Ivan Oleksiyuk, Svyatoslav Voloshynovskiy, Tobias Golling

We introduce a new model for conditional and continuous data morphing called TRansport Adversarial Network for Smooth InTerpolation (TRANSIT). We apply it to create a background da…

hep-ph2024

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…

hep-ph2022★ 27 cited

What's Anomalous in LHC Jets?

Thorsten Buss, Barry M. Dillon, Thorben Finke +5

Searches for anomalies are a significant motivation for the LHC and help define key analysis steps, including triggers. We discuss specific examples how LHC anomalies can be define…

hep-ph2021★ 99 cited

Autoencoders for unsupervised anomaly detection in high energy physics

Thorben Finke, Michael Krämer, Alessandro Morandini +2

Autoencoders are widely used in machine learning applications, in particular for anomaly detection. Hence, they have been introduced in high energy physics as a promising tool for…