2 papers
stat.ML2025
Sparse Techniques for Regression in Deep Gaussian Processes
Jonas Latz, Aretha L. Teckentrup, Simon Urbainczyk
Gaussian processes (GPs) have gained popularity as flexible machine learning models for regression and function approximation with an in-built method for uncertainty quantification…
math.NA2025
Deep Gaussian Process Priors for Bayesian Image Reconstruction
Jonas Latz, Aretha L. Teckentrup, Simon Urbainczyk
In image reconstruction, an accurate quantification of uncertainty is of great importance for informed decision making. Here, the Bayesian approach to inverse problems can be used:…