Amortized Bayesian Multilevel Models
Multilevel Neural Posterior Estimation (ML-NPE) addresses slow Markov Chain Monte Carlo methods for complex multilevel models. It uses deep generative neural networks, specifically normalizing flows, to create an amortized approach where posterior inference becomes a fast forward pass through the network. This allows for near-instantaneous sampling and efficient handling of hierarchical data.