When having a single vector you use an MLP neural network
When having a 2D structure you use a CNN neural network
When having a sequence you use a RNN neural network
Now you have preprocessed an instance and the result is a tree structure.
Let's say for simplicity that the tree structure is always the same tree; only the node values differ among instances.
What kind of neural network architecture would be required to consume the information of a tree structure but also leveraging the connections between the tree nodes?