77 citations · 108 across the 7 of their papers we have counts for
3 papers · 1 filter
Seq-U-Net: A One-Dimensional Causal U-Net for Efficient Sequence Modelling
Daniel Stoller, Mi Tian, Sebastian Ewert +1
Convolutional neural networks (CNNs) with dilated filters such as the Wavenet or the Temporal Convolutional Network (TCN) have shown good results in a variety of sequence modelling…
Adaptive Loss Scaling for Mixed Precision Training
Ruizhe Zhao, Brian Vogel, Tanvir Ahmed
Mixed precision training (MPT) is becoming a practical technique to improve the speed and energy efficiency of training deep neural networks by leveraging the fast hardware support…
Deep Neural Network Approximation for Custom Hardware: Where We've Been, Where We're Going
Erwei Wang, James J. Davis, Ruizhe Zhao +5
Deep neural networks have proven to be particularly effective in visual and audio recognition tasks. Existing models tend to be computationally expensive and memory intensive, howe…