If you’re using a continuous sampler like Hamiltonian Monte Carlo (including NUTS), then you have to be careful about cutting derivatives. The problem is that when you reduce a continuous variable to a discrete value (e.g., by rounding or thresholding), you break the connection between the log density and the continuous variables because the gradients become either 1 or undefined.