Model Parameter Generation for Correlated Time Series Forecasting

Research output

Research output per year 2018 2018 2021 2021

• 2 Article in proceeding

Research output per year

Research output per year

Search results

• 2021

  EnhanceNet: Plugin Neural Networks for Enhancing Correlated Time Series Forecasting

  Cirstea, R. G., Kieu, T., Guo, C., Yang, B. & Pan, S. J., Apr 2021, Proceedings of the 37th IEEE International Conference on Data Engineering, ICDE 2021. IEEE (Institute of Electrical and Electronics Engineers), p. 1739-1750 12 p. 9458855. (Proceedings - International Conference on Data Engineering, Vol. 2021-April).

  Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

  • Temporal Dynamic 100%
  • Neural Network 100%
  • Recurrent Neural Network 66%
  • forecasting accuracy 66%
  • Graph Convolution 66%
  52 Citations (Scopus)
• 2018

  Correlated Time Series Forecasting using Multi-Task Deep Neural Networks

  Cirstea, R.-G., Micu, D.-V., Muresan, G.-M., Guo, C. & Yang, B., 17 Oct 2018, CIKM '18 Proceedings of the 27th ACM International Conference on Information and Knowledge Management. Paton, N., Candan, S., Wang, H., Allan, J., Agrawal, R., Labrinidis, A., Cuzzocrea, A., Zaki, M., Srivastava, D., Broder, A. & Schuster, A. (eds.). Association for Computing Machinery (ACM), p. 1527-1530 4 p.

  Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

  • Deep Neural Network 100%
  • Convolutional Neural Network 100%
  • Multi-task Deep Neural Network 100%
  • Correlated Time Series 100%
  • Recurrent Neural Network 66%
  65 Citations (Scopus)