3 citations · 3 across the 3 of their papers we have counts for
3 papers
Fin-Fed-OD: Federated Outlier Detection on Financial Tabular Data
Dayananda Herurkar, Sebastian Palacio, Ahmed Anwar +2
Anomaly detection in real-world scenarios poses challenges due to dynamic and often unknown anomaly distributions, requiring robust methods that operate under an open-world assumpt…
Explaining Anomalies using Denoising Autoencoders for Financial Tabular Data
Timur Sattarov, Dayananda Herurkar, Jörn Hees
Recent advances in Explainable AI (XAI) increased the demand for deployment of safe and interpretable AI models in various industry sectors. Despite the latest success of deep neur…
RECol: Reconstruction Error Columns for Outlier Detection
Jörn Hees, Dayananda Herurkar, Mario Meier
Detecting outliers or anomalies is a common data analysis task. As a sub-field of unsupervised machine learning, a large variety of approaches exist, but the vast majority treats t…