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Future directions

This is a collection of ideas for future directions of this project, mainly intended to keep track of suggestions. The ideas may ideally be executed through funding channels such as GSOC

Enhancements and Differentiators

  • Provide alternate penalty functions e.g. Tikhonov regularizers for the L2 part of the loss function: very useful for time series models
  • Implement group lasso/ group elastic net: very useful to regularize in groups
  • Implement SGD variants by potentially integrating with sklearn: useful for big data
  • Make a contribution to Spark's MLLib: useful for streaming data

Use cases

  • Interface with companion packages such as proposed Spykes and NeuroSTRF to demonstrate use cases for neural data
  • Interface with big functional neural data as Jeremy Freeman's mouse or zerbrafish datasets.