Mat\'ern Kernel

The Matérn kernel is a widely used covariance function in Gaussian process models, crucial for quantifying uncertainty in machine learning applications involving structured data like graphs and manifolds. Current research focuses on extending its use to more complex data structures (e.g., cellular complexes) and improving the understanding of its properties within various model architectures, including investigations into kernel mixtures and identifiability issues. This work is significant because it enhances the accuracy and interpretability of Gaussian process models, impacting fields like healthcare and astronomy where uncertainty quantification is paramount, particularly in active learning scenarios with costly data acquisition.