/GRNN.keras

Keras Implementation of Grounded RNN

Primary LanguagePython

Keras Implementation of Grounded RNNs

This is a implementation of Grounded RNNs as proposed by Ankit Vani, et. al

I have modified the GRU and Dense Layers of Keras into Grounded_GRU and Grounded_Dense respectively to add the functionality mentioned in the paper.

The main modifications in these layers are as follows:

  • GRU
    • Multiplied the recurrent weight matrices, which correspond to the label states of the hidden vector, with an identity matrix to convert all non-diagonal elements to zero.
    • WARNING: My implementation only supports GRU models with implementation parameter set to 2
  • Dense
    • Performs an inverse sigmoid operation on the grounded vector and then applies the affine transformation. For more details refer to

TODO

  • Add sample implementation for sequence classification.