Optimal uncertainty bounds for multivariate kernel regression under bounded noise: A Gaussian process-based dual function
DGX agentarXiv:2603.16481v2 Announce Type: replace Abstract: Non-conservative uncertainty bounds are essential for making reliable predictions about latent functions from noisy data, and thus, a key enabler fo