> estimator built out of a DAG of calculations

All loops can be modeled as a DAG and single attached piece of memory (of sufficient width) allowed to execute to a steady state; sorry if it wasn't clear that I was talking about things like NTMs too. (It's why I used 'tensor network' most places; also, in practice, we tend to let subgraphs reach a steady state independently where possible.)

Your comment is also an excellent example of a strawman: you picked out the word 'DAG' to raise a technical argument when the usage of DAG versus general tensor networks clearly wasn't the main point (as some NNs have feedback and the standard model is posed as differential equations).

It's more constructive to respond to the strongest point, not pick at technical details that can easily be rephrased.