@inproceedings{epprod41,
       booktitle = {Fifth Australian Conference on Neural Networks},
           month = {["lib/utils:month\verb1_141" not defined]},
           title = {Neural Transplant Surgery: An Approach to Pre-training Recurrent Networks},
          author = {P Vamplew and A Adams},
            year = {1994},
        keywords = {recurrent neural networks, pre-training, weight initialisation},
             url = {http://eprints.utas.edu.au/41/},
        abstract = {Partially-recurrent networks have advantages over strictly feed-forward networks for certain spatiotemporal pattern classification or prediction tasks. However networks involving recurrent links are generally more difficult to train than their non-recurrent counterparts. In this paper we demonstrate that the costs of training a recurrent network can be greatly reduced by initialising the network prior to training with weights 'transplanted' from a non-recurrent architecture.}
}