Let Me Explain What I Did or What I Would Have Done: An Empirical Study on the Effects of Explanations and Person-Likeness on Trust in and Understanding of Algorithms.

[BibT_eX]

[DOI]

Jessica M. Szczuka

Aike C. Horstmann

Proceedings of the 13th Nordic Conference on Human-Computer Interaction, 2024

Challenges, Methods, Data-A Survey of Machine Learning in Water Distribution Networks.

[BibT_eX]

[DOI]

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2024, 2024

Application of Multi-Instance Counterfactual Explanation in Road Safety Analysis.

[BibT_eX]

[DOI]

André Artelt

Andreas Gregoriades

Proceedings of the Thirteenth International Workshop on Agents in Traffic and Transportation co-located with the the 27th European Conference on Artificial Intelligence (ECAI 2024), 2024

2023

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

[BibT_eX]

[DOI]

Appl. Artif. Intell., December, 2023

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

[BibT_eX]

[DOI]

André Artelt

Roel Visser

Barbara Hammer

Neurocomputing, November, 2023

Contrasting Explanations for Understanding and Regularizing Model Adaptations.

[BibT_eX]

[DOI]

Neural Process. Lett., October, 2023

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

[BibT_eX]

[DOI]

Ulrike Kuhl

André Artelt

Barbara Hammer

Frontiers Comput. Sci., 2023

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

[BibT_eX]

[DOI]

Ulrike Kuhl

André Artelt

Barbara Hammer

Proceedings of the Explainable Artificial Intelligence, 2023

Unsupervised Unlearning of Concept Drift with Autoencoders.

[BibT_eX]

[DOI]

André Artelt

Kleanthis Malialis

Christos G. Panayiotou

Marios M. Polycarpou

Barbara Hammer

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2023

Adversarial Attacks on Leakage Detectors in Water Distribution Networks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Computational Intelligence, 2023

Spatial Graph Convolution Neural Networks for Water Distribution Systems.

[BibT_eX]

[DOI]

Proceedings of the Advances in Intelligent Data Analysis XXI, 2023

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

[BibT_eX]

[DOI]

André Artelt

Alexander Schulz

Barbara Hammer

Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods, 2023

"How to Make Them Stay?": Diverse Counterfactual Explanations of Employee Attrition.

[BibT_eX]

[DOI]

André Artelt

Andreas Gregoriades

Proceedings of the 25th International Conference on Enterprise Information Systems, 2023

2022

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

[BibT_eX]

[DOI]

André Artelt

Barbara Hammer

Neurocomputing, 2022

"Explain it in the Same Way!" - Model-Agnostic Group Fairness of Counterfactual Explanations.

[BibT_eX]

[DOI]

André Artelt

Barbara Hammer

CoRR, 2022

One Explanation to Rule them All - Ensemble Consistent Explanations.

[BibT_eX]

[DOI]

CoRR, 2022

Precise Change Point Detection using Spectral Drift Detection.

[BibT_eX]

[DOI]

CoRR, 2022

"Even if ..." - Diverse Semifactual Explanations of Reject.

[BibT_eX]

[DOI]

André Artelt

Barbara Hammer

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2022

Localization of Concept Drift: Identifying the Drifting Datapoints.

[BibT_eX]

[DOI]

Proceedings of the International Joint Conference on Neural Networks, 2022

Explaining Reject Options of Learning Vector Quantization Classifiers.

[BibT_eX]

[DOI]

Proceedings of the 14th International Joint Conference on Computational Intelligence, 2022

Explainable Artificial Intelligence for Improved Modeling of Processes.

[BibT_eX]

[DOI]

Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2022, 2022

Taking Care of Our Drinking Water: Dealing with Sensor Faults in Water Distribution Networks.

[BibT_eX]

[DOI]

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2022, 2022

SAM-kNN Regressor for Online Learning in Water Distribution Networks.

[BibT_eX]

[DOI]

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2022, 2022

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

[BibT_eX]

[DOI]

Ulrike Kuhl

André Artelt

Barbara Hammer

Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022

Improving Zorro Explanations for Sparse Observations with Dense Proxy Data.

[BibT_eX]

[DOI]

Andreas Mazur

André Artelt

Barbara Hammer