  We propose a simple scheme for merging two neural networks trained with
different starting initialization into a single one with the same size as the
original ones. We do this by carefully selecting channels from each input
network. Our procedure might be used as a finalization step after one tries
multiple starting seeds to avoid an unlucky one. We also show that training two
networks and merging them leads to better performance than training a single
network for an extended period of time.
  Availability: https://github.com/fmfi-compbio/neural-network-merging
