Gaussian Processes and Bayesian Inference
This cluster of papers focuses on the application of Gaussian Processes in machine learning, covering topics such as variational inference, sparse regression, Bayesian inference, deep learning, and probabilistic models. It also explores the use of Gaussian Processes for nonparametric methods, time series modelling, and handling big data.
Papers listed on taxonomy pages are the top few works per node from the OpenAlex snapshot. That list is not exhaustive and is not an endorsement. The topic map and the journal registry remain separate: there is still no authoritative topic-to-venue or topic-to-organization edge. Search is a lexical lookup, not a claim that a venue publishes a topic.