Graph-structured data are pervasive in the real-world such as social networks, molecular graphs and transaction networks.

Recent clinical trials in oncology have used increasingly complex methodologies, such as causal inference methods for intercurrent events, external control, and covariate adjustment, posing challenges ...

Which goes back to the major concern over the Knowledge Graph and publisher’s traffic. Above is another example, now with 6 steps, a description and a link to the publisher’s site.

Human system risk in spaceflight through systematic processes and knowledge graphs developed at the NASA Human System Risk Board (HSRB).

Recently, Quantitative Biology published an approach entitled "Gene Regulatory Network Inference based on Causal Discovery Integrating with Graph Neural Network", that leverages graph ...

There are many simple and apparently plausible, but ultimately fallacious, interpretations of chain graphs that are often invoked, implicitly or explicitly. These interpretations also lead to flawed ...

So the example is not a counterexample to causal decision theory. Nevertheless, the example shows that causal decision theory can recommend unratifiable acts (acts that once decided upon appear ...