PUB - Publikationen an der Universität Bielefeld

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• [6]
  

  2025 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 3001606

  Feldhans, R., & Hammer, B., 2025. Towards Reliable Drift Detection and Explanation in Text Data. In Intelligent Data Engineering and Automated Learning – IDEAL 2024, PT I. Lecture Notes in Computer Science. no.15346 Cham: Springer , pp. 301-312.

  PUB | DOI | WoS
   
• [5]
  

  2023 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2985684

  Kummert, J., et al., 2023. Generating Cardiovascular Data to Improve Training of Assistive Heart Devices. In 2023 IEEE Symposium Series on Computational Intelligence (SSCI). IEEE, pp. 1292-1297.

  PUB | DOI
   
• [4]
  

  2023 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2985683

  Feldhans, R., et al., 2023. Data Augmentation for Cardiovascular Time Series Data Using WaveNet. In 2023 IEEE Symposium Series on Computational Intelligence (SSCI). IEEE, pp. 836-841.

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• [3]
  

  2023 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2983457

  Schroeder, S., et al., 2023. Measuring Fairness with Biased Data: A Case Study on the Effects of Unsupervised Data in Fairness Evaluation. In I. Rojas, G. Joya, & A. Catala, eds. Advances in Computational Intelligence. 17th International Work-Conference on Artificial Neural Networks, IWANN 2023, Ponta Delgada, Portugal, June 19–21, 2023, Proceedings, Part I. Lecture Notes in Computer Science. Cham: Springer Nature Switzerland, pp. 134-145.

  PUB | DOI
   
• [2]
  

  2022 | Zeitschriftenaufsatz | E-Veröff. vor dem Druck | PUB-ID: 2962746

  Artelt, A., et al., 2022. Contrasting Explanations for Understanding and Regularizing Model Adaptations. Neural Processing Letters, 55, p 5273–5297.

  PUB | PDF | DOI | Download (ext.) | WoS
   
• [1]
  

  2021 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2957373

  Artelt, A., et al., 2021. Contrastive Explanations for Explaining Model Adaptations. In I. Rojas, G. Joya, & A. Catala, eds. Advances in Computational Intelligence. 16th International Work-Conference on Artificial Neural Networks, IWANN 2021, Virtual Event, June 16–18, 2021, Proceedings, Part I. Lecture Notes in Computer Science. Cham: Springer , pp. 101-112.

  PUB | DOI