44 citations · 87 across the 30 of their papers we have counts for
4 papers · 2 filters
Bayesian Hierarchical Models For Multi-type Survey Data Using Spatially Correlated Covariates Measured With Error
Saikat Nandy, Scott H. Holan, Jonathan R. Bradley +1
We introduce Bayesian hierarchical models for predicting high-dimensional tabular survey data which can be distributed from one or multiple classes of distributions (e.g., Gaussian…
A Bayesian Spatio-Temporal Level Set Dynamic Model and Application to Fire Front Propagation
Myungsoo Yoo, Christopher K. Wikle
Intense wildfires impact nature, humans, and society, causing catastrophic damage to property and the ecosystem, as well as the loss of life. Forecasting wildfire front propagation…
A Review of Data-Driven Discovery for Dynamic Systems
Joshua S. North, Christopher K. Wikle, Erin M. Schliep
Many real-world scientific processes are governed by complex nonlinear dynamic systems that can be represented by differential equations. Recently, there has been increased interes…
A Bayesian Approach for Spatio-Temporal Data-Driven Dynamic Equation Discovery
Joshua S. North, Christopher K. Wikle, Erin M. Schliep
Differential equations based on physical principals are used to represent complex dynamic systems in all fields of science and engineering. Through repeated use in both academics a…