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poplar v0.2.0

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@cchapmanbird cchapmanbird released this 30 May 11:08
v0.2
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poplar is a lightweight package for performing selection bias modelling with machine learning. It is useful when the selection process can only be modelled at a high computational cost, and is efficient and accurate even at high dimensionality. It is fully implemented with pytorch.

If you find poplar useful in your work, please cite both Chapman-Bird et al. (2023) and the package doi.

Changes in v0.2.0:

  • Fixed a bug that prevented loading of a saved LinearModel on a machine with no GPU available in the slot that the model was originally saved on. Now, models are always moved to CPU prior to pickling.
  • Fixed a bug when using the IdentityRescaler that prevented moving of models to GPU
  • Some documentation changes and other minor bug fixes.
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