5 citations · 13 across the 9 of their papers we have counts for
4 papers · 1 filter
Calibrated Forecasts of Quasi-Periodic Climate Processes with Deep Echo State Networks and Penalized Quantile Regression
Matthew Bonas, Christopher K. Wikle, Stefano Castruccio
Among the most relevant processes in the Earth system for human habitability are quasi-periodic, ocean-driven multi-year events whose dynamics are currently incompletely characteri…
Bayesian Ensemble Echo State Networks for Enhancing Binary Stochastic Cellular Automata
Nicholas Grieshop, Christopher K. Wikle
Binary spatio-temporal data are common in many application areas. Such data can be considered from many perspectives, including via deterministic or stochastic cellular automata, w…
Data-Driven Modeling of Wildfire Spread with Stochastic Cellular Automata and Latent Spatio-Temporal Dynamics
Nicholas Grieshop, Christopher K. Wikle
We propose a Bayesian stochastic cellular automata modeling approach to model the spread of wildfires with uncertainty quantification. The model considers a dynamic neighborhood st…
Using Echo State Networks to Inform Physical Models for Fire Front Propagation
Myungsoo Yoo, Christopher K. Wikle
Wildfires can be devastating, causing significant damage to property, ecosystem disruption, and loss of life. Forecasting the evolution of wildfire boundaries is essential to real-…