The speaker modeled branch and bound as an inference problem where each step from the root to a node is represented by conditional probabilities for choosing left or right.

“And what I did is I from this as a inference problem. But basically I say well if we go down from the root to uh to one of the nodes, you effectively do a conditional probability. Like you you have a probability to choose either left or right. Then you have another to choose in left or right. And that gives you a much more general probel uh much more general model which kind of grows with your problem.”