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• [6]
  

  2025 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 3001606

  Feldhans, R., and 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, vol. 15346, (Cham: Springer ), 301-312.

  PUB | DOI | WoS
   
• [5]
  

  2023 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2985684

  Kummert, J., Schulz, A., Feldhans, R., Habigt, M., Stemmler, M., Kohler, C., Abel, D., Rossaint, R., and Hammer, B. (2023). “Generating Cardiovascular Data to Improve Training of Assistive Heart Devices” in 2023 IEEE Symposium Series on Computational Intelligence (SSCI) (IEEE), 1292-1297.

  PUB | DOI
   
• [4]
  

  2023 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2985683

  Feldhans, R., Schulz, A., Kummert, J., Habigt, M., Stemmler, M., Kohler, C., Abel, D., Rossaint, R., and Hammer, B. (2023). “Data Augmentation for Cardiovascular Time Series Data Using WaveNet” in 2023 IEEE Symposium Series on Computational Intelligence (SSCI) (IEEE), 836-841.

  PUB | DOI
   
• [3]
  

  2023 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2983457

  Schroeder, S., Schulz, A., Tarakanov, I., Feldhans, R., and Hammer, B. (2023). “Measuring Fairness with Biased Data: A Case Study on the Effects of Unsupervised Data in Fairness Evaluation” in Advances in Computational Intelligence. 17th International Work-Conference on Artificial Neural Networks, IWANN 2023, Ponta Delgada, Portugal, June 19–21, 2023, Proceedings, Part I, Rojas, I., Joya, G., and Catala, A. eds. Lecture Notes in Computer Science (Cham: Springer Nature Switzerland), 134-145.

  PUB | DOI
   
• [2]
  

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

  Artelt, A., Hinder, F., Vaquet, V., Feldhans, R., and Hammer, B. (2022). Contrasting Explanations for Understanding and Regularizing Model Adaptations. Neural Processing Letters 55, 5273–5297.

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

  2021 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2957373

  Artelt, A., Hinder, F., Vaquet, V., Feldhans, R., and Hammer, B. (2021). “Contrastive Explanations for Explaining Model Adaptations” 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., and Catala, A. eds. Lecture Notes in Computer Science (Cham: Springer ), 101-112.

  PUB | DOI