211 citations · 409 across the 11 of their papers we have counts for
5 papers · 1 filter
Delta Networks for Optimized Recurrent Network Computation
Daniel Neil, Jun Haeng Lee, Tobi Delbruck +1
Many neural networks exhibit stability in their activation patterns over time in response to inputs from sensors operating under real-world conditions. By capitalizing on this prop…
Phased LSTM: Accelerating Recurrent Network Training for Long or Event-based Sequences
Daniel Neil, Michael Pfeiffer, Shih-Chii Liu
Recurrent Neural Networks (RNNs) have become the state-of-the-art choice for extracting patterns from temporal sequences. However, current RNN models are ill-suited to process irre…
Steering a Predator Robot using a Mixed Frame/Event-Driven Convolutional Neural Network
Diederik Paul Moeys, Federico Corradi, Emmett Kerr +5
This paper describes the application of a Convolutional Neural Network (CNN) in the context of a predator/prey scenario. The CNN is trained and run on data from a Dynamic and Activ…
Precise neural network computation with imprecise analog devices
Jonathan Binas, Daniel Neil, Giacomo Indiveri +2
The operations used for neural network computation map favorably onto simple analog circuits, which outshine their digital counterparts in terms of compactness and efficiency. Neve…
A Curriculum Learning Method for Improved Noise Robustness in Automatic Speech Recognition
Stefan Braun, Daniel Neil, Shih-Chii Liu
The performance of automatic speech recognition systems under noisy environments still leaves room for improvement. Speech enhancement or feature enhancement techniques for increas…