arXiv stat.ML
· Papers
Integrating Neural Encoders in Bayesian Generalized Linear Mixed Models for Multimodal Data
arXiv:2607.04647v1 Announce Type: new Abstract: Scalable Bayesian inference for generalized linear mixed models (GLMMs) provides uncertainty-aware analysis of correlated longitudinal data, but existing scalable approaches largely assume low-dimensional tabular predictors and do not directly accommodate high-dimensional