Deep Neural Networks for Large-scale Complex Spatial and Spatio-temporal Processes
Date:
Authors: P. Nag
Environmental statistics play a critical role in various interconnected domains, encompassing weather and climate forecasting, air quality monitoring, and sustainable urban planning. However, because of their high inherent unpredictability and nonstationarity, modeling complex spatio-temporal dynamics of environmental processes are challenging. This dissertation develops a set of DNN based methods for large-scale spatial and spatio-temporal processes.