Author

Jae-Hyun Kim

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Preprint Oct 2026

Finite-Rank Logistic Gaussian Processes with Exact Likelihood for Conditional Density Estimation

Conditional density estimation describes how the entire distribution of a response changes with covariates, and in imaging studies also with location. Logistic Gaussian processes (LGP) give a flexible prior for such densities. However, the normalizing constant of an LGP has no closed form, so existing methods approxima...

Jae-Hyun Kim, Indrajit Ghosh, D. Pati et al. · 1 citation

Preprint Sep 2026

Isotonic surrogate modeling for computer experiments with many input variables

Virtual simulators are widely used for studying complex physical phenomena, from particle collisions to rocket propulsion. Such"computer experiments"can be highly time-intensive, and a Bayesian surrogate model can be used for efficient emulation with reliable uncertainty quantification. To train accurate surrogates wit...

Jae-Hyun Kim, Simon Mak · 0 citations