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Missing data is a common occurrence in the time series domain, for instance due to faulty sensors, server downtime or patients not attending their scheduled appointments. One of the best methods to impute these missing values is Multiple Imputations by Chained Equations (MICE) which has the drawback that it can only model linear relationships among the variables in a multivariate time series. The advancement of deep learning and its ability to model non-linear relationships among variables makedoi:10.1007/978-3-030-44584-3_1 dblp:conf/ida/SafiBUS20 fatcat:ohmm3kxiyzgwth7od2t6grlvp4