  We present an implementation of tree neural networks within the proof
assistant HOL4. Their architecture makes them naturally suited for
approximating functions whose domain is a set of formulas. We measure the
performance of our implementation and compare it with other machine learning
predictors on the tasks of evaluating arithmetical expressions and estimating
the truth of propositional formulas.
