In many research papers there are 'projection layers' related to BLSTM layers. For example, from here:

"we trained an 8-layer BLSTM encoder including 320 cells in each layer and direction, and the linear projection layer with 320 units followed by each BLSTM layer"

I can't understand what this means and how it works.

Any help on this topic would be appreciated. Thanks in advance!


1 Answer 1


A "projection" is a simple linear/dense layer, that is, a matrix multiplication and a bias vector addition.

It is called projection because you "project" a representation of dimensionality $M$ into a representation space of dimensionality $N$.

Sometimes, especially for sequences or 2D data, these projections are implemented as a convolution of size 1, which is equivalent to the computations I described above.

  • $\begingroup$ Thanks for your answer, but I have another question because it's a little bit ambiguous for me, are they used for the dimensionality reduction? $\endgroup$
    – Selma_KA
    Dec 24, 2020 at 14:19
  • $\begingroup$ A projection can be used to decrease the dimensionality of the representation, but it can as well be used to increase the dimensionality. $\endgroup$
    – noe
    Dec 24, 2020 at 14:22

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