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K. J. H. Law

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#machine learning Preprint Oct 2026

Theoretical and Practical Advances in Hierarchical Bayesian Deep Learning Methodology

This work introduces the multilevel particle marginal Metropolis-Hastings (MLPMMH) method, which combines pseudo-marginal inference for the hyperparameters with coupled sequential Monte Carlo (SMC) across hierarchy of network-width truncations for conditional parameter inference.

N. K. Chada, S. Cotter, K. J. H. Law et al. · 0 citations