GP4IEQ_spatiotemporal is a public repository dedicated to exploring and modeling spatiotemporal data using Gaussian Processes (GPs). The project focuses on applications in Indoor Environmental Quality (IEQ), leveraging advanced GP techniques to analyze and predict environmental variables across space and time.
This repository provides Jupyter Notebooks, datasets, and scripts for reproducible research and experimentation.
- Autoregressive Gaussian Process Models: Implementations and experiments with autoregressive GPs for temporal and spatiotemporal prediction.
- Spatiotemporal Analysis: Notebooks demonstrating the modeling of spatial, temporal, and combined spatiotemporal patterns in IEQ data.
- Reproducible Research: All code and data are organized for easy reproduction of results and further exploration.
- Modular Structure: Clear separation of data, models, and analysis to facilitate understanding and extension.