Quantum causal models: the merits of the spirit of Reichenbach’s principle for understanding quantum causal structure

A Finite Axiomatisation of Finite-State Automata Using String Diagrams

“…In [73], the authors give a diagrammatic account of interventions and a sufficient criterion to identify when a given causal effect can be reliably estimated from observational data, see Figure 7. The recent [84] extends this work to counterfactuals and shows how causal inference calculations can be carried out fully diagrammatically. Beyond its pedagogical value, one advantage of the diagrammatic approach is that it is axiomatic: as such, it is not restricted to the category of Markov kernels, but applies in all categories with the relevant structure.…”