BRNN-GAN: Generative Adversarial Networks with Bi-directional Recurrent Neural Networks for Multivariate Time Series Imputation. Wu, Z., Ma, C., Shi, X., Wu, L., Zhang, D., Tang, Y., & Stojmenovic, M. In 27th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2021, Beijing, China, December 14-16, 2021, pages 217–224, 2021. IEEE.
BRNN-GAN: Generative Adversarial Networks with Bi-directional Recurrent Neural Networks for Multivariate Time Series Imputation [link]Paper  doi  bibtex   
@inproceedings{DBLP:conf/icpads/WuMSWZTS21,
  author       = {Zejun Wu and
                  Chao Ma and
                  Xiaochuan Shi and
                  Libing Wu and
                  Dian Zhang and
                  Yutian Tang and
                  Milos Stojmenovic},
  title        = {{BRNN-GAN:} Generative Adversarial Networks with Bi-directional Recurrent
                  Neural Networks for Multivariate Time Series Imputation},
  booktitle    = {27th {IEEE} International Conference on Parallel and Distributed Systems,
                  {ICPADS} 2021, Beijing, China, December 14-16, 2021},
  pages        = {217--224},
  publisher    = {{IEEE}},
  year         = {2021},
  url          = {https://doi.org/10.1109/ICPADS53394.2021.00033},
  doi          = {10.1109/ICPADS53394.2021.00033},
  timestamp    = {Mon, 09 May 2022 09:35:52 +0200},
  biburl       = {https://dblp.org/rec/conf/icpads/WuMSWZTS21.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

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