64 citations · 64 across the 1 of their papers we have counts for
3 papers
Brightening the Optical Flow through Posit Arithmetic
Vinay Saxena, Ankitha Reddy, Jonathan Neudorfer +4
As new technologies are invented, their commercial viability needs to be carefully examined along with their technical merits and demerits. The posit data format, proposed as a dro…
Performance-Efficiency Trade-off of Low-Precision Numerical Formats in Deep Neural Networks
Zachariah Carmichael, Hamed F. Langroudi, Char Khazanov +3
Deep neural networks (DNNs) have been demonstrated as effective prognostic models across various domains, e.g. natural language processing, computer vision, and genomics. However,…
Deep Positron: A Deep Neural Network Using the Posit Number System
Zachariah Carmichael, Hamed F. Langroudi, Char Khazanov +3
The recent surge of interest in Deep Neural Networks (DNNs) has led to increasingly complex networks that tax computational and memory resources. Many DNNs presently use 16-bit or…