Preprint Open access
Scalable Logistic Gaussian Process Density Regression with Kinetic Langevin Sampling
Conditional density estimation targets the full distribution of a response given covariates, as required, for example, for per-galaxy photometric redshifts. We develop a scalable Bayesian estimator based on the logistic Gaussian process. The log conditional density has a separable covariance: a Matérn kernel along the …