Converting age and sex variables to a 64-unit dense layer I am studying a preprint for my own learning (https://www.medrxiv.org/content/medrxiv/early/2020/04/27/2020.04.23.20067967.full.pdf) and I am befuddled by the following detail of the neural network architecture:

This is in accord with the paper's description of the architecture (p. 5):

Age and sex were input into a 64-unit hidden layer and was concatenated with the other branches.

How can the two scalars of age and sex be implemented as a 64-unit dense layer?
Convert them into numbers (using one-hot vectors or direct numerical representations) and then concatenate them. Then, you can pass them through the Dense layer.