2 papers
stat.ML2018
Recurrent Deep Divergence-based Clustering for simultaneous feature learning and clustering of variable length time series
Daniel J. Trosten, Andreas S. Strauman, Michael Kampffmeyer +1
The task of clustering unlabeled time series and sequences entails a particular set of challenges, namely to adequately model temporal relations and variable sequence lengths. If t…
cs.NE2017
Classification of postoperative surgical site infections from blood measurements with missing data using recurrent neural networks
Andreas Storvik Strauman, Filippo Maria Bianchi, Karl Øyvind Mikalsen +3
Clinical measurements that can be represented as time series constitute an important fraction of the electronic health records and are often both uncertain and incomplete. Recurren…