424 citations · 920 across the 4 of their papers we have counts for
4 papers
EPNAS: Efficient Progressive Neural Architecture Search
Yanqi Zhou, Peng Wang, Sercan Arik +4
In this paper, we propose Efficient Progressive Neural Architecture Search (EPNAS), a neural architecture search (NAS) that efficiently handles large search space through a novel p…
Deep Learning Scaling is Predictable, Empirically
Joel Hestness, Sharan Narang, Newsha Ardalani +6
Deep learning (DL) creates impactful advances following a virtuous recipe: model architecture search, creating large training data sets, and scaling computation. It is widely belie…
Block-Sparse Recurrent Neural Networks
Sharan Narang, Eric Undersander, Gregory Diamos
Recurrent Neural Networks (RNNs) are used in state-of-the-art models in domains such as speech recognition, machine translation, and language modelling. Sparsity is a technique to…
Deep Voice: Real-time Neural Text-to-Speech
Sercan O. Arik, Mike Chrzanowski, Adam Coates +9
We present Deep Voice, a production-quality text-to-speech system constructed entirely from deep neural networks. Deep Voice lays the groundwork for truly end-to-end neural speech…