PUB - Publikationen an der Universität Bielefeld

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• [5]
  

  2024 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2993740

  Vaquet V, Hinder F, Vaquet J, Lammers K, Quakernack L, Hammer B (2024)
  Localizing of Anomalies in Critical Infrastructure using Model-Based Drift Explanations.
  In: 2024 International Joint Conference on Neural Networks (IJCNN). IEEE: 1-8.

  PUB | DOI | WoS
   
• [4]
  

  2024 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2993739

  Vaquet V, Hinder F, Artelt A, Ashraf I, Strotherm J, Vaquet J, Brinkrolf J, Hammer B (2024)
  Challenges, Methods, Data–A Survey of Machine Learning in Water Distribution Networks.
  In: Artificial Neural Networks and Machine Learning – ICANN 2024. 33rd International Conference on Artificial Neural Networks, Lugano, Switzerland, September 17–20, 2024, Proceedings, Part IX. Wand M, Malinovská K, Schmidhuber J, Tetko IV (Eds); Lecture Notes in Computer Science, Cham: Springer Nature Switzerland: 155-170.

  PUB | DOI | WoS
   
• [3]
  

  2024 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2993744

  Vaquet V, Vaquet J, Hinder F, Malialis K, Panayiotou C, Polycarpou M, Hammer B (2024)
  Self-Supervised Learning from Incrementally Drifting Data Streams.
  In: ESANN 2024 proceesdings. Louvain-la-Neuve (Belgium): Ciaco - i6doc.com: 431-436.

  PUB | DOI
   
• [2]
  

  2024 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2992337

  Zanutto D, Michalopoulos C, Chatzistefanou G-A, Vamvakeridou-Lyroudia L, Tsiami L, Glynis K, Samartzis P, Hermes L, Hinder F, Vaquet J, Vaquet V, Eliades D, Polycarpou M, Koundouri P, Hammer B, Savić D (2024)
  A Water Futures Approach on Water Demand Forecasting with Online Ensemble Learning.
  In: The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024). Basel Switzerland: MDPI: 60.

  PUB | PDF | DOI
   
• [1]
  

  2021 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2960687

  Vaquet V, Hinder F, Vaquet J, Brinkrolf J, Hammer B (2021)
  Online Learning on Non-Stationary Data Streams for Image Recognition using Deep Embeddings.
  IEEE Symposium Series on Computational Intelligence: 1-7.

  PUB | DOI