Efficient Deep Gaussian Process Surrogates via Mini-Batch Latent MAP Estimation
arXiv:2610.38038v1 Announce Type: new Abstract: Deep Gaussian processes (DGPs) are flexible surrogate models for computer experiments with nonstationary response surfaces, but inference over their latent representations remains computationally challenging. Existing methods typically rely on variati…
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- 2026-10-30 04:00 · arXiv stat.ML
Efficient Deep Gaussian Process Surrogates via Mini-Batch Latent MAP Estimation
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