14 citations · 14 across the 3 of their papers we have counts for
4 papers
Exploiting Separability in Multi-Scale Grey-Box Bayesian Optimization
Joshua E. Hammond, Tyler A. Soderstrom, Brian A. Korgel +1
We consider grey-box optimization problems where the decision variables naturally partition into black-box variables (as arguments to an expensive black-box function) and white-box…
Using the SEKF to Transfer NN Models of Dynamical Systems with Limited Data
Joshua E. Hammond, Tyler A. Soderstrom, Brian A. Korgel +1
Data-driven models of dynamical systems require extensive amounts of training data. For many practical applications, gathering sufficient data is not feasible due to cost or safety…
Staying Alive: Online Neural Network Maintenance and Systemic Drift
Joshua E. Hammond, Tyler Soderstrom, Brian A. Korgel +1
We present the Subset Extended Kalman Filter (SEKF) as a method to update previously trained model weights online rather than retraining or finetuning them when the system a model…
Short-Term Solar Irradiance Forecasting Under Data Transmission Constraints
Joshua Edward Hammond, Ricardo A. Lara Orozco, Michael Baldea +1
We report a data-parsimonious machine learning model for short-term forecasting of solar irradiance. The model inputs include sky camera images that are reduced to scalar features…