5 papers
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…
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…
Neutrino Oscillation Parameter Estimation Using Structured Hierarchical Transformers
Giorgio Morales, Gregory Lehaut, Antonin Vacheret +2
Neutrino oscillations encode fundamental information about neutrino masses and mixing parameters, offering a unique window into physics beyond the Standard Model. Estimating these…
Towards Uncertainty Quantification in Generative Model Learning
Giorgio Morales, Frederic Jurie, Jalal Fadili
While generative models have become increasingly prevalent across various domains, fundamental concerns regarding their reliability persist. A crucial yet understudied aspect of th…
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…