I’m trying to express a generative model where gaussian processes are interspersed with parametric distributions. I followed along with the tutorial here, but didn’t see a clear way to adapt the implementation to what I’m trying to do.

Here’s some pseudo code that I hope will clarify the kind of generative process I’m trying to express.

```
f ~ GaussianProcess()
for i in range(n):
U[i] ~ Uniform(0,1)
X[i] ~ f(U[i])
Y[i] ~ Uniform(X[i], X[i] + 1)
observe(Y == y_obs)
```

Thanks!