1.1k citations · 2.2k across the 33 of their papers we have counts for
5 papers · 1 filter
EdgeDRNN: Enabling Low-latency Recurrent Neural Network Edge Inference
Chang Gao, Antonio Rios-Navarro, Xi Chen +2
This paper presents a Gated Recurrent Unit (GRU) based recurrent neural network (RNN) accelerator called EdgeDRNN designed for portable edge computing. EdgeDRNN adopts the spiking…
Thermodynamic Computing
Tom Conte, Erik DeBenedictis, Natesh Ganesh +36
The hardware and software foundations laid in the first half of the 20th Century enabled the computing technologies that have transformed the world, but these foundations are now u…
FaSNet: Low-latency Adaptive Beamforming for Multi-microphone Audio Processing
Yi Luo, Enea Ceolini, Cong Han +2
Beamforming has been extensively investigated for multi-channel audio processing tasks. Recently, learning-based beamforming methods, sometimes called \textit{neural beamformers},…
Closing the Accuracy Gap in an Event-Based Visual Recognition Task
Bodo Rückauer, Nicolas Känzig, Shih-Chii Liu +2
Mobile and embedded applications require neural networks-based pattern recognition systems to perform well under a tight computational budget. In contrast to commonly used synchron…
Reducing state updates via Gaussian-gated LSTMs
Matthew Thornton, Jithendar Anumula, Shih-Chii Liu
Recurrent neural networks can be difficult to train on long sequence data due to the well-known vanishing gradient problem. Some architectures incorporate methods to reduce RNN sta…