3 papers
stat.ML2026
Neural Generalized Mixed-Effects Models
Yuli Slavutsky, Sebastian Salazar, David M. Blei
Generalized linear mixed-effects models (GLMMs) are widely used to analyze grouped and hierarchical data. In a GLMM, each response is assumed to follow an exponential-family distri…
stat.ML2025
Input Adaptive Bayesian Model Averaging
Yuli Slavutsky, Sebastian Salazar, David M. Blei
This paper studies prediction with multiple candidate models, where the goal is to combine their outputs. This task is especially challenging in heterogeneous settings, where diffe…
cs.LG2024
Posterior Mean Matching: Generative Modeling through Online Bayesian Inference
Sebastian Salazar, Michal Kucer, Yixin Wang +2
This paper introduces posterior mean matching (PMM), a new method for generative modeling that is grounded in Bayesian inference. PMM uses conjugate pairs of distributions to model…