Drift-Aware Evaluation of Fair Stream Learning

Lammers K, Hinder F, Hammer B, Vaquet V (2026)
In: ESANN 2026 proceesdings. Louvain-la-Neuve (Belgium): Ciaco - i6doc.com: 127-132.

Causal Explanation of Concept Drift – A Truly Actionable Approach

Komnick D, Lammers K, Hammer B, Vaquet V, Hinder F (2026)
In: Machine Learning and Principles and Practice of Knowledge Discovery in Databases. International Workshops of ECML PKDD 2025, Porto, Portugal, September 15–19, 2025, Revised Selected Papers, Part IV. Koprinska I, Mendes-Moreira J, Branco P (Eds); Communications in Computer and Information Science, 2842. Cham: Springer Nature Switzerland: 396-412.

Realistic Benchmarks for Fair Stream Learning

Lammers K, Vaquet V, Vaquet J, Hammer B (2026)
In: Neural Information Processing. 32nd International Conference, ICONIP 2025, Okinawa, Japan, November 20–24, 2025, Proceedings, Part III. Taniguchi T, Leung CSA, Kozuno T, Yoshimoto J, Mahmud M, Doborjeh M, Doya K (Eds); Communications in Computer and Information Science. Singapore: Springer Nature Singapore: 169-184.

Continuous Fair SMOTE – Fairness-Aware Stream Learning from Imbalanced Data

Lammers K, Vaquet V, Hammer B (2025)
In: Artificial Neural Networks and Machine Learning – ICANN 2025. 34th International Conference on Artificial Neural Networks, Kaunas, Lithuania, September 9–12, 2025, Proceedings, Part I. Senn W, Sanguineti M, Saudargiene A, Tetko IV, Villa AEP, Jirsa V, Bengio Y (Eds); Lecture Notes in Computer Science. Cham: Springer Nature Switzerland: 336-348.

Realistic Benchmarks for Fair Stream Learning

Lammers K, Vaquet V, Vaquet J, Hammer B (Submitted) .

Localizing of Anomalies in Critical Infrastructure using Model-Based Drift Explanations

Vaquet V, Hinder F, Vaquet J, Lammers K, Quakernack L, Hammer B (2024)
In: 2024 International Joint Conference on Neural Networks (IJCNN). IEEE: 1-8.