Christian Mayr

Efficient recurrent architectures through activity sparsity and sparse back-propagation through time

Recurrent neural networks (RNNs) are well suited for solving sequence tasks in resource-constrained systems due to their expressivity and low computational requirements. However, there is still a need to bridge the gap between what RNNs are capable of in terms of efficiency and performance and real…