  AUTOMAP is a promising generalized reconstruction approach, however, it is
not scalable and hence the practicality is limited. We present dAUTOMAP, a
novel way for decomposing the domain transformation of AUTOMAP, making the
model scale linearly. We show dAUTOMAP outperforms AUTOMAP with significantly
fewer parameters.
