Gaussian Processes

Gaussian processes are a powerful machine learning framework applicable to tasks such as regression, classification, and inference. By modeling unknown functions as stochastic processes, they make the training outputs a joint Gaussian random variable, thereby leveraging its statistical properties to infer the function mean and variance under test inputs. This approach has the advantages of efficient prediction and hyperparameter optimization.