Imputing Missing Data In Large-Scale Multivariate Biomedical Wearable Recordings Using Bidirectional Recurrent Neural Networks With Temporal Activation Regularization. Feng, T. and 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