64 citations · 64 across the 2 of their papers we have counts for
4 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…
Asymptotic approximations for symmetric elliptic integrals
Bille C. Carlson, John L. Gustafson
Symmetric elliptic integrals, which have been used as replacements for Legendre's integrals in recent integral tables and computer codes, are homogeneous functions of three or four…