Work

Reassessing Unsupervised Anomaly Augmentation for Fraud Detection: The Roles of Distribution Shift, Learner Instability, and Run-to-Run Variability (code and results)

Year: 2026

Type: software

Abstract: Archived release for Zenodo DOI.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.22977318

Authors: Aslanyürek, Murat, Aslanyürek, Canan

Institution: Kırklareli University

Language: English

Topic: Anomaly Detection Techniques and Applications

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W7214456379

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