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Published May 27, 2020 | Version 1
Software Open

Exploring Clinical Time Series Forecasting with Meta-Features in Variational Recurrent Models

  • 1. University of Leiden
  • 2. NEC Laboratories GmBH
  • 3. Honda Research Institute Europe GmBH

Description

This is the source code used in the following paper:

Ullah, S., Xu, Z., Wang, H., Menzel, S., Sendhoff, B., "Exploring Clinical Time Series Forecasting with Meta-Features in Variational Recurrent Models"  2020 IEEE World Congress on Computational Intelligence 

This paper investigates the effectiveness of Supplementary Medical Information, for improving the prediction of Variational Recurrent Models in Clinical Time Series Forecasting.  

Files

VRNN-TSForecasting-Code-200131-Open.zip

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Additional details

Funding

ECOLE – Experience-based Computation: Learning to Optimise 766186
European Commission