Pu­bli­ka­tio­nen

[ 2022 ] [ 2021 ] [ 2020 ]

2022 [ nach oben ]

  • 1.
    Nivarthi, C.P., Vogt, S., Sick, B.: Unified Autoencoder with Task Embeddings for Multi-Task Learning in Renewable Power Forecasting. International Conference on Machine Learning and Applications (ICMLA). IEEE (2022).
     
  • 2.
    Nivarthi, C.P.: Transfer Learning as an Essential Tool for Digital Twins in Renewable Energy Systems. In: Tomforde, S. en Krupitzer, C. (reds.) Organic Computing -- Doctoral Dissertation Colloquium 2021. bll. 47–59. kassel university press (2022).
     

2021 [ nach oben ]

  • 1.
    Gruhl, C., Hannan, A., Huang, Z., Nivarthi, C., Vogt, S.: The Problem with Real-World Novelty Detection -- Issues in Multivariate Probabilistic Models. Workshop on Self-Improving System Integration (SISSY), ACSOS. bll. 204–209. IEEE (2021).
     

2020 [ nach oben ]

  • 1.
    Singh, A., Nivarthi, C.P., Akhilesh, K.B.: Implementing IoT in India---A Look at Macro Issues and a Framework for Recommendations. In: Akhilesh, K.B. en Möller, D.P.F. (reds.) Smart Technologies : Scope and Applications. bll. 35–52. Springer (2020).
     
  • 2.
    Nivarthi, C.P., Akhilesh, K.B.: Cybercare---Role of Cyber Security in Healthcare Industry. In: Akhilesh, K.B. en Möller, D.P.F. (reds.) Smart Technologies : Scope and Applications. bll. 291–304. Springer (2020).