André Artelt

aartelt@techfak.uni-bielefeld.de
ORCID logo https://orcid.org/0000-0002-2426-3126

PEVZ-ID
170245986

41 Publikationen

Alle markieren

  • [41]
    2024 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2993831
    J.M. Szczuka, et al., “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”, NordiCHI '24: Proceedings of the 13th Nordic Conference on Human-Computer Interaction, Association for Computing Machinery, ed., New York, USA: 2024.
    PUB | DOI | Download (ext.) | WoS
     
  • [40]
    2024 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2993739
    V. Vaquet, et al., “Challenges, Methods, Data–A Survey of Machine Learning in Water Distribution Networks”, Artificial Neural Networks and Machine Learning – ICANN 2024. 33rd International Conference on Artificial Neural Networks, Lugano, Switzerland, September 17–20, 2024, Proceedings, Part IX, M. Wand, et al., eds., Lecture Notes in Computer Science, Cham: Springer Nature Switzerland, 2024, pp.155-170.
    PUB | DOI | WoS
     
  • [39]
    2024 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2994227
    A. Artelt, et al., “EPyT-Flow: A Toolkit for Generating Water DistributionNetwork Data”, Journal of Open Source Software, vol. 9, 2024, : 7104.
    PUB | DOI
     
  • [38]
    2024 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2990768
    A. Artelt and A. Gregoriades, “Supporting organizational decisions on How to improve customer repurchase using multi-instance counterfactual explanations”, Decision Support Systems, vol. 182, 2024, : 114249.
    PUB | DOI | WoS
     
  • [37]
    2024 | Bielefelder E-Dissertation | PUB-ID: 2985769 OA
    A. Artelt, Contrasting Explanations in Machine Learning. Efficiency, Robustness & Applications, Bielefeld: Universität Bielefeld, 2024.
    PUB | PDF | DOI
     
  • [36]
    2023 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2984049
    M.I. Ashraf, et al., “Spatial Graph Convolution Neural Networks for Water Distribution Systems”, Advances in Intelligent Data Analysis XXI. 21st International Symposium on Intelligent Data Analysis, IDA 2023, Louvain-la-Neuve, Belgium, April 12–14, 2023, Proceedings, B. Crémilleux, S. Hess, and S. Nijssen, eds., Lecture Notes in Computer Science, Cham: Springer Nature Switzerland, 2023, pp.29-41.
    PUB | DOI
     
  • [35]
    2023 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2983795
    U. Kuhl, A. Artelt, and B. Hammer, “For Better or Worse: The Impact of Counterfactual Explanations’ Directionality on User Behavior in xAI”, Explainable Artificial Intelligence. First World Conference, xAI 2023, Lisbon, Portugal, July 26–28, 2023, Proceedings, Part III, L. Longo, ed., Communications in Computer and Information Science, Cham: Springer Nature Switzerland, 2023, pp.280-300.
    PUB | DOI | WoS
     
  • [34]
    2023 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2979026
    J. Jakob, et al., “Interpretable SAM-kNN Regressor for Incremental Learning on High-Dimensional Data Streams”, Applied Artificial Intelligence, vol. 37, 2023, : 2198846.
    PUB | DOI | WoS
     
  • [33]
    2023 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2969734 OA
    U. Kuhl, A. Artelt, and B. Hammer, “Let's go to the Alien Zoo: Introducing an experimental framework to study usability of counterfactual explanations for machine learning”, Frontiers in Computer Science, vol. 5, 2023, : 1087929.
    PUB | PDF | DOI | Download (ext.) | WoS | arXiv
     
  • [32]
    2023 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2969383
    A. Artelt, A. Schulz, and B. Hammer, “"Why Here and not There?": Diverse Contrasting Explanations of Dimensionality Reduction”, Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods, Setúbal, Portugal: SCITEPRESS - Science and Technology Publications, 2023, pp.27-38.
    PUB | DOI | arXiv
     
  • [31]
    2023 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2985571
    A. Artelt, et al., “Unsupervised Unlearning of Concept Drift with Autoencoders”, 2023 IEEE Symposium Series on Computational Intelligence (SSCI), IEEE, 2023, pp.703-710.
    PUB | DOI
     
  • [30]
    2023 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2983728
    A. Artelt, R. Visser, and B. Hammer, “"I do not know! but why?"- Local model-agnostic example-based explanations of reject”, Neurocomputing, vol. 558, 2023, : 126722.
    PUB | DOI | WoS
     
  • [29]
    2023 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2983406
    P. Stahlhofen, et al., “Adversarial Attacks on Leakage Detectors in Water Distribution Networks”, Advances in Computational Intelligence. 17th International Work-Conference on Artificial Neural Networks, IWANN 2023, Ponta Delgada, Portugal, June 19–21, 2023, Proceedings, Part II, I. Rojas, G. Joya, and A. Catala, eds., Lecture Notes in Computer Science, Cham: Springer Nature Switzerland, 2023, pp.451-463.
    PUB | DOI | Preprint
     
  • [28]
    2022 | Zeitschriftenaufsatz | E-Veröff. vor dem Druck | PUB-ID: 2962746 OA
    A. Artelt, et al., “Contrasting Explanations for Understanding and Regularizing Model Adaptations”, Neural Processing Letters, vol. 55, 2022, pp. 5273–5297.
    PUB | PDF | DOI | Download (ext.) | WoS
     
  • [27]
    2022 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2969736
    U. Kuhl, A. Artelt, and B. Hammer, “Keep Your Friends Close and Your Counterfactuals Closer: Improved Learning From Closest Rather Than Plausible Counterfactual Explanations in an Abstract Setting”, 2022 ACM Conference on Fairness, Accountability, and Transparency, New York, NY, USA: ACM, 2022, pp.2125-2137.
    PUB | DOI | Download (ext.)
     
  • [26]
    2022 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2969461
    A. Artelt and B. Hammer, ““Even if …” – Diverse Semifactual Explanations of Reject”, 2022 IEEE Symposium Series on Computational Intelligence (SSCI), H. Ishibuchi, ed., Piscataway, NJ: IEEE, 2022, pp.854-859.
    PUB | DOI
     
  • [25]
    2022 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2967296
    R. Velioglu, et al., “Explainable Artificial Intelligence for Improved Modeling of Processes”, Intelligent Data Engineering and Automated Learning – IDEAL 2022. 23rd International Conference, IDEAL 2022, Manchester, UK, November 24–26, 2022, Proceedings, H. Yin, D. Camacho, and P. Tino, eds., Lecture Notes in Computer Science, vol. 13756, Cham: Springer International Publishing, 2022, pp.313-325.
    PUB | DOI
     
  • [24]
    2022 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2969459
    J. Jakob, et al., “SAM-kNN Regressor for Online Learning in Water Distribution Networks”, Artificial Neural Networks and Machine Learning – ICANN 2022. 31st International Conference on Artificial Neural Networks, Bristol, UK, September 6–9, 2022, Proceedings, Part III, E. Pimenidis, et al., eds., Lecture Notes in Computer Science, vol. 13531, Cham: Springer Nature , 2022, pp.752-762.
    PUB | DOI
     
  • [23]
    2022 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2969460
    A. Artelt, et al., “Explaining Reject Options of Learning Vector Quantization Classifiers”, Proceedings of the 14th International Joint Conference on Computational Intelligence, SCITEPRESS - Science and Technology Publications, 2022, pp.249-261.
    PUB | DOI
     
  • [22]
    2022 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2966088
    F. Hinder, et al., “Localization of Concept Drift: Identifying the Drifting Datapoints”, 2022 International Joint Conference on Neural Networks (IJCNN), IEEE, 2022, pp.1-9.
    PUB | DOI | Download (ext.)
     
  • [21]
    2022 | Report | Veröffentlicht | PUB-ID: 2965286
    A. Artelt, et al., Faire Algorithmen und die Fairness von Erklärungen: Informatische, rechtliche und ethische Perspektiven, DuEPublico: Duisburg-Essen Publications online, University of Duisburg-Essen, Germany, 2022.
    PUB | DOI | Download (ext.)
     
  • [20]
    2022 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2962650 OA
    V. Vaquet, et al., “Taking care of our drinking water: Dealing with Sensor Faults in Water Distribution Networks”, Presented at the 31st International Conference on Artificial Neural Networks, Bristol, 2022.
    PUB | PDF
     
  • [19]
    2022 | Kurzbeitrag Konferenz / Poster | PUB-ID: 2962861
    F. Hinder, et al., “Localization of Concept Drift: Identifying the Drifting Datapoints”, 2022.
    PUB
     
  • [18]
    2022 | Preprint | PUB-ID: 2962919 OA
    A. Artelt, et al., “One Explanation to Rule them All — Ensemble Consistent Explanations”, ArXiv:2205.08974 , 2022.
    PUB | PDF | Download (ext.) | arXiv
     
  • [17]
    2021 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2957340
    A. Artelt and B. Hammer, “Efficient computation of counterfactual explanations and counterfactual metrics of prototype-based classifiers”, Neurocomputing, vol. 470, 2021, pp. 304-317.
    PUB | DOI | Download (ext.) | WoS
     
  • [16]
    2021 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2957373
    A. Artelt, et al., “Contrastive Explanations for Explaining Model Adaptations”, Advances in Computational Intelligence. 16th International Work-Conference on Artificial Neural Networks, IWANN 2021, Virtual Event, June 16–18, 2021, Proceedings, Part I, I. Rojas, G. Joya, and A. Catala, eds., Lecture Notes in Computer Science, Cham: Springer , 2021, pp.101-112.
    PUB | DOI
     
  • [15]
    2021 | Preprint | PUB-ID: 2959899
    A. Artelt and B. Hammer, “Convex optimization for actionable & plausible counterfactual explanations”, arXiv: 2105.07630v1, 2021.
    PUB | Download (ext.) | arXiv
     
  • [14]
    2021 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2962747
    A. Artelt, et al., “Evaluating Robustness of Counterfactual Explanations”, 2021 IEEE Symposium Series on Computational Intelligence (SSCI), Piscataway, NJ: IEEE, 2021, pp.01-09.
    PUB | DOI
     
  • [13]
    2021 | Report | Veröffentlicht | PUB-ID: 2954239
    J. Szczuka, et al., Können Kinder aufgeklärte Nutzer* innen von Sprachassistenten sein? Rechtliche, psychologische, ethische und informatische Perspektiven, Essen: Universität Duisburg-Essen, Universitätsbibliothek, 2021.
    PUB | DOI
     
  • [12]
    2021 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2957588
    A. Artelt and B. Hammer, “Efficient computation of contrastive explanations”, 2021 International Joint Conference on Neural Networks (IJCNN), New York: Institute of Electrical and Electronics Engineers (IEEE), 2021, pp.1-9.
    PUB | DOI | Download (ext.)
     
  • [11]
    2020 | Konferenzbeitrag | PUB-ID: 2946488
    F. Hinder, A. Artelt, and B. Hammer, “Towards non-parametric drift detection via Dynamic Adapting Window Independence Drift Detection (DAWIDD)”, Proceedings of the 37th International Conference on Machine Learning, 2020.
    PUB | Download (ext.)
     
  • [10]
    2020 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2946685
    A. Artelt and B. Hammer, “Efficient computation of counterfactual explanations of LVQ models”, ESANN 2020 - proceedings, M. Verleysen, ed., Louvain-la-Neuve: Ciaco , 2020, pp.19-24.
    PUB | Download (ext.)
     
  • [9]
    2020 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2946761
    A. Artelt and B. Hammer, “Convex Density Constraints for Computing Plausible Counterfactual Explanations”, Artificial Neural Networks and Machine Learning - ICANN 2020 - 29th International Conference on Artificial Neural Networks, Bratislava, Slovakia, September 15-18, 2020, Proceedings, Part {I}, I. Farkas, P. Masulli, and S. Wermter, eds., Lecture Notes in Computer Science, vol. 12396, Cham: Springer, 2020, pp.353-365.
    PUB | DOI | Download (ext.)
     
  • [8]
    2020 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2945878
    C.L. Geminn, et al., “Kinder als Nutzende smarter Sprachassistenten Spezieller Gestaltungsbedarf zum Schutz von Kindern”, Datenschutz und Datensicherheit - DuD, vol. 44, 2020, pp. 600-605.
    PUB | DOI | Download (ext.)
     
  • [7]
    2020 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2957814
    N. Krämer, et al., “Improving and Evaluating Conversational User Interfaces for Children”, IUI '20: Proceedings of the 25th International Conference on Intelligent User Interfaces, New York: Association for Computing Machinery, 2020.
    PUB
     
  • [6]
    2019 | Kurzbeitrag Konferenz / Poster | PUB-ID: 2935044 OA
    A. Artelt, J. Jakob, and V. Vaquet, “Continuous online user authentication based on keystroke dynamics”, Presented at the Interdisciplinary College (IK), Günne/Möhnesee, Germany, 2019.
    PUB | Dateien verfügbar
     
  • [5]
    2019 | Preprint | PUB-ID: 2959898
    A. Artelt and B. Hammer, “On the computation of counterfactual explanations - A survey”, arXiv: 1911.07749v1, 2019.
    PUB | Download (ext.) | arXiv
     
  • [4]
    2019 | Datenpublikation | PUB-ID: 2936468 OA
    A. Artelt, CEML - Counterfactuals for Explaining Machine Learning models - A Python toolbox , Bielefeld University, 2019.
    PUB | Dateien verfügbar | DOI
     
  • [3]
    2019 | Monographie | PUB-ID: 2935200 OA
    B. Paaßen, A. Artelt, and B. Hammer, Lecture Notes on Applied Optimization, Faculty of Technology, Bielefeld University: 2019.
    PUB | Dateien verfügbar
     
  • [2]
    2019 | Report | Veröffentlicht | PUB-ID: 2937888
    N. Krämer, et al., KI-basierte Sprachassistenten im Alltag: Forschungsbedarf aus informatischer, psychologischer, ethischer und rechtlicher Sicht, Universität Duisburg-Essen, Universitätsbibliothek, 2019.
    PUB | DOI | Download (ext.)
     
  • [1]
    2019 | Monographie | PUB-ID: 2936408 OA
    A. Artelt, Introduction to Machine Learning - Supplementary notes, 2019.
    PUB | PDF
     
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