Contrasting Explanations in Machine Learning. Efficiency, Robustness & Applications

Artelt A (2024)
Bielefeld: Universität Bielefeld.

Let's go to the Alien Zoo: Introducing an experimental framework to study usability of counterfactual explanations for machine learning

Kuhl U, Artelt A, Hammer B (2023)
Frontiers in Computer Science 5: 1087929.

Unsupervised Unlearning of Concept Drift with Autoencoders

Artelt A, Malialis K, Panayiotou CG, Polycarpou MM, Hammer B (2023)
In: 2023 IEEE Symposium Series on Computational Intelligence (SSCI). IEEE: 703-710.

Spatial Graph Convolution Neural Networks for Water Distribution Systems

Ashraf I, Hermes L, Artelt A, Hammer B (2023)
In: Advances in Intelligent Data Analysis XXI. 21st International Symposium on Intelligent Data Analysis, IDA 2023, Louvain-la-Neuve, Belgium, April 12–14, 2023, Proceedings. Crémilleux B, Hess S, Nijssen S (Eds); Lecture Notes in Computer Science. Cham: Springer Nature Switzerland: 29-41.

For Better or Worse: The Impact of Counterfactual Explanations’ Directionality on User Behavior in xAI

Kuhl U, Artelt A, Hammer B (2023)
In: Explainable Artificial Intelligence. First World Conference, xAI 2023, Lisbon, Portugal, July 26–28, 2023, Proceedings, Part III. Longo L (Ed); Communications in Computer and Information Science. Cham: Springer Nature Switzerland: 280-300.

"I do not know! but why?"- Local model-agnostic example-based explanations of reject

Artelt A, Visser R, Hammer B (2023)
Neurocomputing 558: 126722.

Adversarial Attacks on Leakage Detectors in Water Distribution Networks

Stahlhofen P, Artelt A, Hermes L, Hammer B (2023)
In: Advances in Computational Intelligence. 17th International Work-Conference on Artificial Neural Networks, IWANN 2023, Ponta Delgada, Portugal, June 19–21, 2023, Proceedings, Part II. Rojas I, Joya G, Catala A (Eds); Lecture Notes in Computer Science. Cham: Springer Nature Switzerland: 451-463.

Interpretable SAM-kNN Regressor for Incremental Learning on High-Dimensional Data Streams

Jakob J, Artelt A, Hasenjäger M, Hammer B (2023)
Applied Artificial Intelligence 37(1): 2198846.

"Why Here and not There?": Diverse Contrasting Explanations of Dimensionality Reduction

Artelt A, Schulz A, Hammer B (2023)
In: Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods. Setúbal, Portugal: SCITEPRESS - Science and Technology Publications: 27-38.

Contrasting Explanations for Understanding and Regularizing Model Adaptations

Artelt A, Hinder F, Vaquet V, Feldhans R, Hammer B (2022)
Neural Processing Letters 55: 5273–5297.

Faire Algorithmen und die Fairness von Erklärungen: Informatische, rechtliche und ethische Perspektiven

Artelt A, Geminn C, Hammer B, Manzeschke A, Mavrina L, Weber C (2022)
DuEPublico: Duisburg-Essen Publications online, University of Duisburg-Essen, Germany.

Localization of Concept Drift: Identifying the Drifting Datapoints

Hinder F, Vaquet V, Brinkrolf J, Artelt A, Hammer B (2022)
In: 2022 International Joint Conference on Neural Networks (IJCNN). IEEE: 1-9.

SAM-kNN Regressor for Online Learning in Water Distribution Networks

Jakob J, Artelt A, Hasenjäger M, Hammer B (2022)
In: Artificial Neural Networks and Machine Learning – ICANN 2022. 31st International Conference on Artificial Neural Networks, Bristol, UK, September 6–9, 2022, Proceedings, Part III. Pimenidis E, Angelov P, Jayne C, Papaleonidas A, Aydin M (Eds); Lecture Notes in Computer Science, 13531. Cham: Springer Nature : 752-762.

“Even if …” – Diverse Semifactual Explanations of Reject

Artelt A, Hammer B (2022)
In: 2022 IEEE Symposium Series on Computational Intelligence (SSCI). Ishibuchi H (Ed); Piscataway, NJ: IEEE: 854-859.

Explaining Reject Options of Learning Vector Quantization Classifiers

Artelt A, Brinkrolf J, Visser R, Hammer B (2022)
In: Proceedings of the 14th International Joint Conference on Computational Intelligence. SCITEPRESS - Science and Technology Publications: 249-261.

Keep Your Friends Close and Your Counterfactuals Closer: Improved Learning From Closest Rather Than Plausible Counterfactual Explanations in an Abstract Setting

Kuhl U, Artelt A, Hammer B (2022)
In: 2022 ACM Conference on Fairness, Accountability, and Transparency. New York, NY, USA: ACM: 2125-2137.

Localization of Concept Drift: Identifying the Drifting Datapoints

Hinder F, Vaquet V, Brinkrolf J, Artelt A, Hammer B (2022) .

One Explanation to Rule them All — Ensemble Consistent Explanations

Artelt A, Vrachimis S, Eliades D, Polycarpou M, Hammer B (2022)
ArXiv:2205.08974 .

Taking care of our drinking water: Dealing with Sensor Faults in Water Distribution Networks

Vaquet V, Artelt A, Brinkrolf J, Hammer B (2022)
Presented at the 31st International Conference on Artificial Neural Networks, Bristol.

Explainable Artificial Intelligence for Improved Modeling of Processes

Velioglu R, Göpfert JP, Artelt A, Hammer B (2022)
In: Intelligent Data Engineering and Automated Learning – IDEAL 2022. 23rd International Conference, IDEAL 2022, Manchester, UK, November 24–26, 2022, Proceedings. Yin H, Camacho D, Tino P (Eds); Lecture Notes in Computer Science, 13756. Cham: Springer International Publishing: 313-325.

Convex optimization for actionable & plausible counterfactual explanations

Artelt A, Hammer B (2021)
arXiv: 2105.07630v1.

Efficient computation of contrastive explanations

Artelt A, Hammer B (2021)
In: 2021 International Joint Conference on Neural Networks (IJCNN). New York: Institute of Electrical and Electronics Engineers (IEEE): 1-9.

Contrastive Explanations for Explaining Model Adaptations

Artelt A, Hinder F, Vaquet V, Feldhans R, Hammer B (2021)
In: Advances in Computational Intelligence. 16th International Work-Conference on Artificial Neural Networks, IWANN 2021, Virtual Event, June 16–18, 2021, Proceedings, Part I. Rojas I, Joya G, Catala A (Eds); Lecture Notes in Computer Science. Cham: Springer : 101-112.

Können Kinder aufgeklärte Nutzer* innen von Sprachassistenten sein? Rechtliche, psychologische, ethische und informatische Perspektiven

Szczuka J, Artelt A, Geminn C, Hammer B, Kopp S, Manzeschke A, Rossnagel A, Slawik P, Strathmann C, Szymczyk N, Varonina L, et al. (2021)
Essen: Universität Duisburg-Essen, Universitätsbibliothek.

Efficient computation of counterfactual explanations and counterfactual metrics of prototype-based classifiers

Artelt A, Hammer B (2021)
Neurocomputing 470(VSI: ESANN 2020): 304-317.

Evaluating Robustness of Counterfactual Explanations

Artelt A, Vaquet V, Velioglu R, Hinder F, Brinkrolf J, Schilling M, Hammer B (2021)
In: 2021 IEEE Symposium Series on Computational Intelligence (SSCI). Piscataway, NJ: IEEE: 01-09.

Improving and Evaluating Conversational User Interfaces for Children

Krämer N, Szczuka J, Rossnagel A, Geminn C, Kopp S, Hammer B, Mavrina L, Artelt A, Manzeschke A, Weber C (2020)
In: IUI '20: Proceedings of the 25th International Conference on Intelligent User Interfaces. New York: Association for Computing Machinery.

Kinder als Nutzende smarter Sprachassistenten Spezieller Gestaltungsbedarf zum Schutz von Kindern

Geminn CL, Szczuka J, Weber C, Artelt A, Varonina L (2020)
Datenschutz und Datensicherheit - DuD 44(9): 600-605.

Towards non-parametric drift detection via Dynamic Adapting Window Independence Drift Detection (DAWIDD)

Hinder F, Artelt A, Hammer B (2020)
In: Proceedings of the 37th International Conference on Machine Learning.

Efficient computation of counterfactual explanations of LVQ models

Artelt A, Hammer B (2020)
In: ESANN 2020 - proceedings. Verleysen M (Ed); Louvain-la-Neuve: Ciaco : 19-24.

Convex Density Constraints for Computing Plausible Counterfactual Explanations

Artelt A, Hammer B (2020)
In: Artificial Neural Networks and Machine Learning - ICANN 2020 - 29th International Conference on Artificial Neural Networks, Bratislava, Slovakia, September 15-18, 2020, Proceedings, Part {I}. Farkas I, Masulli P, Wermter S (Eds); Lecture Notes in Computer Science, 12396. Cham: Springer: 353-365.

On the computation of counterfactual explanations - A survey

Artelt A, Hammer B (2019)
arXiv: 1911.07749v1.

CEML - Counterfactuals for Explaining Machine Learning models - A Python toolbox

Artelt A (2019)
Bielefeld University.

Continuous online user authentication based on keystroke dynamics

Artelt A, Jakob J, Vaquet V (2019)
Presented at the Interdisciplinary College (IK), Günne/Möhnesee, Germany.

Lecture Notes on Applied Optimization

Paaßen B, Artelt A, Hammer B (2019)
Faculty of Technology, Bielefeld University.

KI-basierte Sprachassistenten im Alltag: Forschungsbedarf aus informatischer, psychologischer, ethischer und rechtlicher Sicht

Krämer N, Artelt A, Geminn C, Hammer B, Kopp S, Manzeschke A, Rossnagel A, Slawik P, Szczuka J, Varonina L, Weber C (2019)
Universität Duisburg-Essen, Universitätsbibliothek.

Introduction to Machine Learning - Supplementary notes

Artelt A (2019) .