M. Sc. Yujiang He
AI for Computationally Intelligent Systems (AI4CIS)
- Telefon
- +49 561 804-6184
- Yujiang.he[at]uni-kassel[dot]de
- Standort
- Wilhelmshöher Allee 67
34121 Kassel
- Raum
- 1106
Publikationen
2024[ to top ]
- Time-Series Representation Learning via Heterogeneous Spatial-Temporal Contrasting for Remaining Useful Life Prediction. . In International Conference on Pattern Recognition (ICPR). 2024.
- PrOuD: Probabilistic Outlier Detection Solution for Time Series Analysis on Real-world Photovoltaic Inverters. . In Energies (MDPI), 17(1), bl 64. MDPI, 2024.
2023[ to top ]
- Spatio-Temporal Attention Graph Neural Network for Remaining Useful Life Prediction. . In Computational Science and Computational Intelligence (CSCI), bll 99–105. IEEE, 2023.
- Active Learning with Fast Model Updates and Class-Balanced Selection for Imbalanced Datasets. . In Workshop on Interactive Adapative Learning (IAL), ECML PKDD, bll 28–45. 2023.
2022[ to top ]
- Design of Explainability Module with Experts in the Loop for Visualization and Dynamic Adjustment of Continual Learning. . In Workshop on Interactive Machine Learning Workshop (IMLW), AAAI, bll 1–6. 2022.
- Adaptive Explainable Continual Learning Framework for Regression Problems with Focus on Power Forecasts. . 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. . In Workshop on Interactive Adaptive Learning (IAL), ECML PKDD. 2021.
- Toward Application of Continuous Power Forecasts in a Regional Flexibility Market. . In International Joint Conference on Neural Networks (IJCNN), bll 1–8. IEEE, 2021.
- CLeaR: An adaptive continual learning framework for regression tasks. . In AI Perspectives, 3(1), bl 2. Springer, 2020.
2020[ to top ]
- Forecasting Power Grid States for Regional Energy Markets with Deep Neural Networks. . In International Joint Conference on Neural Networks (IJCNN). IEEE, 2020.
- Continuous Learning of Deep Neural Networks to Improve Forecasts for Regional Energy Markets. . 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. . In International Conference on Mobile Ubiquitous Computing, Systems, Services and Technologies (UBICOMM). IARIA, 2017.