What are the main differences between approximate bayesian computation vs approximate bayesian inference?
Are they essentially the same?
Do they refer to the same of different family of models?
My initial understanding was that bayesian computataions refer to approaches that are used when the likelihood or analytic form of the formulation is intractable and that bayesian inference was for methods when the posterior is intractable?
Am I thinking this wrong?