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greenelab / tybalt

Training and evaluating a variational autoencoder for pan-cancer gene expression data
BSD 3-Clause "New" or "Revised" License
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Adding option to tie ADAGE weights together #123

Closed gwaybio closed 6 years ago

gwaybio commented 6 years ago

The original ADAGE used tied weights (and was written in Theano). The previous ADAGE version in this repo did not have a tied weights constraint (meaning that the encoder and decoder weights were free to vary independently). We observed relatively poor performance of ADAGE models compared to other compression techniques (see simulation_results.md and z_dimensions_hyperparameter_sweep_results.md). We hypothesized that one of the reasons could be because of the lack of ADAGE tied weights.

There used to be an option to tie weights in the Keras autoencoder class (keras-team/keras#180, keras-team/keras#3261) but this has since been removed.

The pull request adds this functionality as a custom layer and also modifies the DataModel class to use these options.

gwaybio commented 6 years ago

Thanks for comments @danich1 and @jaclyn-taroni - ready for re-review