1 citations · 1 across the 1 of their papers we have counts for
3 papers
cs.LG2020
A Fortran-Keras Deep Learning Bridge for Scientific Computing
Jordan Ott, Mike Pritchard, Natalie Best +3
Implementing artificial neural networks is commonly achieved via high-level programming languages like Python and easy-to-use deep learning libraries like Keras. These software lib…
cs.SE2020★ 1 cited
Exploring the Efficacy of Transfer Learning in Mining Image-Based Software Artifacts
Natalie Best, Jordan Ott, Erik Linstead
Transfer learning allows us to train deep architectures requiring a large number of learned parameters, even if the amount of available data is limited, by leveraging existing mode…
cs.LG2019
Learning in the Machine: To Share or Not to Share?
Jordan Ott, Erik Linstead, Nicholas LaHaye +1
Weight-sharing is one of the pillars behind Convolutional Neural Networks and their successes. However, in physical neural systems such as the brain, weight-sharing is implausible.…