Bayesian networks are probabilistic graphical models that encode conditional dependencies among variables within a directed acyclic graph. In the context of causal inference, these networks provide a ...

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Artificial intelligence owes a lot of its smarts to Judea Pearl. In the 1980s he led efforts that allowed machines to reason probabilistically. Now he’s one of the field’s sharpest critics. In his ...

A study on high-concurrency payment systems proposes a distributed architecture with layered consistency control to balance transaction accuracy and scalability. By decoupling system components and ...