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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. 2024 International Joint Conference on Neural Networks (IJCNN), 1-8. IEEE. https://doi.org/10.1109/IJCNN60899.2024.10651472

  PUB | DOI | WoS
   
• [4]
  

  2024 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2993739

  Vaquet, V., Hinder, F., Artelt, A., Ashraf, I., Strotherm, J., Vaquet, J., Brinkrolf, J., et al. (2024). Challenges, Methods, Data–A Survey of Machine Learning in Water Distribution Networks. In M. Wand, K. Malinovská, J. Schmidhuber, & I. V. Tetko (Eds.), Lecture Notes in Computer Science. Artificial Neural Networks and Machine Learning – ICANN 2024. 33rd International Conference on Artificial Neural Networks, Lugano, Switzerland, September 17–20, 2024, Proceedings, Part IX (pp. 155-170). Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-72356-8_11

  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. ESANN 2024 proceesdings, 431-436. Louvain-la-Neuve (Belgium): Ciaco - i6doc.com. https://doi.org/10.14428/esann/2024.ES2024-49

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• [2]
  

  2024 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2992337

  Zanutto, D., Michalopoulos, C., Chatzistefanou, G. - A., Vamvakeridou-Lyroudia, L., Tsiami, L., Glynis, K., Samartzis, P., et al. (2024). A Water Futures Approach on Water Demand Forecasting with Online Ensemble Learning. The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024), 60. Basel Switzerland: MDPI. https://doi.org/10.3390/engproc2024069060

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• [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. https://doi.org/10.1109/SSCI50451.2021.9659903

  PUB | DOI