Convolutional Networks for Fast, Energy-Efficient Neuromorphic Computing
DVS Benchmark Datasets for Object Tracking, Action Recognition, and Object Recognition
Re-architecting the on-chip memory sub-system of machine-learning accelerator for embedded devices
Low Precision RNNs: Quantizing RNNs Without Losing Accuracy
Shift: A Zero FLOP, Zero Parameter Alternative to Spatial Convolutions
Conversion of artificial recurrent neural networks to spiking neural networks for low-power neuromorphic hardware