We elaborate on an alternative representation of conditional probability to the usual tree diagram. We term the representation “turtleback diagram” for its resemblance to the pattern on turtle shells.

When we have a situation where we are considering several events, it is beneficial to have a way of representing it visually. Tree diagrams are visual representations of the outcomes of events. Robin ...

ABSTRACT: We elaborate on an alternative representation of conditional probability to the usual tree diagram. We term the representation “turtleback diagram” for its resemblance to the pattern on ...

Two events are independent if the probability of the first event happening has no impact on the probability of the second event happening. For example, the probability of rolling a 6 on a die will not ...

Understanding conditional probability is essential when exploring fields in Machine Learning and Artificial Intelligence. In this lesson, you'll learn about conditional probability, what it is, and ...

Abstract: In this chapter, the authors discuss sample spaces, basic probability theory and random variables. Conditional probability leads to tree diagrams and the Bayes formula. Bernoulli trials pave ...

This is a preview. Log in through your library . Abstract An influence diagram is a graphical representation of a decision problem that is at once a formal description of a decision problem that can ...

For cutting-edge AI researchers looking for clean semantics models to represent the context-specific causal dependencies essential for causal induction, this DeepMind’s algorithm encourages you to ...