In order to deploy Recurrent Neural Networks (RNNs) efficiently, we propose a technique to reduce the parameters of a network by pruning weights during the initial training of the network.
Researchers introduce an automated synaptic connectivity inference pipeline (SyConn) to delivers a richly annotated wiring diagram, or components of a connectome.