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  • vaeST: A Two-Stage Longitudinal Variational Autoencoder for Spatiotemporal Data (Author: Samuel Berchuck)
    • This is supplementary code for the following two manuscripts:
      • Berchuck, S., Mukherjee, S., and Medeiros, F. “Estimating Rates of Progression and Predicting Future Visual Fields in Glaucoma Using a Deep Variational Autoencoder”. Scientific Reports (2019).
      • Berchuck, S., Medeiros, F., and Mukherjee, S. “Scalable Modeling of Spatiotemporal Data using the Variational Autoencoder: an Application in Glaucoma”. Under Revision.
  • spBFA: Spatial Bayesian Factor Analysis (Author: Samuel Berchuck)
    • Berchuck, S., Janko, M., Pan, W., Medeiros, F., and Mukherjee, S. “Bayesian Non-Parametric Factor Analysis for Longitudinal Spatial Surfaces”. Under Revision.

  • spCP: Spatially Varying Change Points (Author: Samuel Berchuck)
    • Berchuck S.I., Mwanza J.C., and Warren J.L. A spatially varying change points model for monitoring glaucoma progression using visual field data, Spatial Statistics (2019).