http://eprints.utas.edu.au/41/ Neural Transplant Surgery: An Approach to Pre-training Recurrent Networks Vamplew, P Adams, A 280200 Artificial Intelligence and Signal and Image Processing 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. 1994 Conference or Workshop Item PeerReviewed application/pdf http://eprints.utas.edu.au/41/1/transplant-acnn94.pdf Vamplew, P and Adams, A (1994) Neural Transplant Surgery: An Approach to Pre-training Recurrent Networks. In: Fifth Australian Conference on Neural Networks, February 1994, University of Queensland. http://eprints.utas.edu.au/41/http://eprints.utas.edu.au/41/1/