Imputing Missing Data In Large-Scale Multivariate Biomedical Wearable Recordings Using Bidirectional Recurrent Neural Networks With Temporal Activation Regularization. Feng, T. & Narayanan, S. S. In 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019, Berlin, Germany, July 23-27, 2019, pages 2529–2534, 2019.
Imputing Missing Data In Large-Scale Multivariate Biomedical Wearable Recordings Using Bidirectional Recurrent Neural Networks With Temporal Activation Regularization [link]Paper  doi  bibtex   
@inproceedings{DBLP:conf/embc/FengN19,
  author    = {Tiantian Feng and
               Shrikanth S. Narayanan},
  title     = {Imputing Missing Data In Large-Scale Multivariate Biomedical Wearable
               Recordings Using Bidirectional Recurrent Neural Networks With Temporal
               Activation Regularization},
  booktitle = {41st Annual International Conference of the {IEEE} Engineering in
               Medicine and Biology Society, {EMBC} 2019, Berlin, Germany, July 23-27,
               2019},
  pages     = {2529--2534},
  year      = {2019},
  crossref  = {DBLP:conf/embc/2019},
  url       = {https://doi.org/10.1109/EMBC.2019.8856966},
  doi       = {10.1109/EMBC.2019.8856966},
  timestamp = {Tue, 03 Dec 2019 00:00:00 +0100},
  biburl    = {https://dblp.org/rec/bib/conf/embc/FengN19},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

Downloads: 0