Using Random Effects to Account for High-Cardinality Categorical Features and Repeated Measures in Deep Neural Networks

A special scenario of interest is that of repeated measures, where the categorical feature is the identity of the individual or object, and each object is measured several times, possibly under different conditions (values of the other features).