1 citations · 1 across the 6 of their papers we have counts for
8 papers
Learning Parametric Nitrogen Fertilizer Response Curves Using Neuro Symbolic Regression
Giorgio Morales, John Sheppard
Accurately modeling crop response to Nitrogen (N) fertilization is a fundamental challenge in precision agriculture, as it impacts both economic returns and environmental sustainab…
Decomposable Neural Symbolic Regression
Giorgio Morales, John W. Sheppard
Symbolic regression (SR) models complex systems by discovering mathematical expressions that capture underlying relationships in observed data. However, most SR methods prioritize…
Risk-Based Prognostics and Health Management
John W. Sheppard
It is often the case that risk assessment and prognostics are viewed as related but separate tasks. This chapter describes a risk-based approach to prognostics that seeks to provid…
Overview of Complex System Design
John W. Sheppard
This chapter serves as an introduction to systems engineering focused on the broad issues surrounding realizing complex integrated systems. What is a system? We pose a number of po…
MicroNAS: An Automated Framework for Developing a Fall Detection System
Seyed Mojtaba Mohasel, John Sheppard, Lindsey K. Molina +3
This work presents MicroNAS, an automated neural architecture search tool specifically designed to create models optimized for microcontrollers with small memory resources. The ESP…
Adaptive Sampling to Reduce Epistemic Uncertainty Using Prediction Interval-Generation Neural Networks
Giorgio Morales, John Sheppard
Obtaining high certainty in predictive models is crucial for making informed and trustworthy decisions in many scientific and engineering domains. However, extensive experimentatio…
Univariate Skeleton Prediction in Multivariate Systems Using Transformers
Giorgio Morales, John W. Sheppard
Symbolic regression (SR) methods attempt to learn mathematical expressions that approximate the behavior of an observed system. However, when dealing with multivariate systems, the…
Counterfactual Analysis of Neural Networks Used to Create Fertilizer Management Zones
Giorgio Morales, John Sheppard
In Precision Agriculture, the utilization of management zones (MZs) that take into account within-field variability facilitates effective fertilizer management. This approach enabl…