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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, 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, 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, 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, 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, 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, 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, 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, Catala A (Eds); Lecture Notes in Computer Science, Cham: Springer : 101-112.

  PUB | DOI