Gaussian Random Fields

Gaussian Random Fields (GRFs) are mathematical models used to describe how values vary continuously across a space or time, where the entire set of values has a joint Gaussian (normal) distribution. Think of them as a way to predict the likelihood of different patterns in phenomena like terrain elevation, temperature distribution, or sensor data. In a GRF, nearby points tend to have similar values, and the overall behavior is governed by certain statistical rules (mean and variance). They are powerful tools in fields like geostatistics, machine learning, and environmental modeling to analyze and simulate complex spatial or temporal data.