2022[ to top ]
  • Adaptive Explainable Continual Learning Framework for Regression Problems with Focus on Power Forecasts. He, Yujiang. In Organic Computing -- Doctoral Dissertation Colloquium 2021, S. Tomforde, C. Krupitzer (reds.), bll 125–140. kassel university press, 2022.
2021[ to top ]
  • Uncertainty and Utility Sampling with Pre-Clustering. Huang, Zhixin; He, Yujiang; Vogt, Stephan; Sick, Bernhard. In Workshop on Interactive Adaptive Learning (IAL), ECML PKDD. 2021.
  • Toward Application of Continuous Power Forecasts in a Regional Flexibility Market. He, Yujiang; Huang, Zhixin; Sick, Bernhard. In International Joint Conference on Neural Networks (IJCNN), bll 1–8. IEEE, 2021.
2020[ to top ]
  • Forecasting Power Grid States for Regional Energy Markets with Deep Neural Networks. He, Y.; Henze, J.; Sick, B. In International Joint Conference on Neural Networks (IJCNN). IEEE, 2020.
  • Continuous Learning of Deep Neural Networks to Improve Forecasts for Regional Energy Markets. He, Yujiang; Henze, Janosch; Sick, Bernhard. In International Federation of Automatic Control (IFAC) World Congress, bll 12175–12182. Elsevier, 2020.
2017[ to top ]
  • TPM Framework: a Comprehensive Kit for Exploring Applications with Textile Pressure Mapping Matrix. Zhou, Bo; Cheng, Jingyuan; Mawandia, Ankur; He, Yujiang; Huang, Zhixin; Sundholm, Mathias; Yildrim, Muhammet; Cruz, Heber; Lukowicz, Paul. In International Conference on Mobile Ubiquitous Computing, Systems, Services and Technologies (UBICOMM). IARIA, 2017.