15 citations · 32 across the 20 of their papers we have counts for
3 papers · 1 filter
Bridging the Band Gap: What Device Physicists Need to Know About Machine Learning
Nathaniel Tye, Stephan Hofmann, Phillip Stanley-Marbell
This article surveys the landscape of semiconductor materials and devices research for the acceleration of machine learning (ML) algorithms. We observe a disconnect between the sem…
Machine Learning for Sensor Transducer Conversion Routines
Thomas Newton, James T. Meech, Phillip Stanley-Marbell
Sensors with digital outputs require software conversion routines to transform the unitless analogue-to-digital converter samples to physical quantities with correct units. These c…
An Algorithm for Sensor Data Uncertainty Quantification
James T. Meech, Phillip Stanley-Marbell
This article presents an algorithm for reducing measurement uncertainty of one physical quantity when given oversampled measurements of two physical quantities with correlated nois…