Probabilistic Inference Task

A Probabilistic Inference Task is an inference task of deriving the probability of one or more random variables taking a specific value or set of values.

• Context:
  • It can be solved by a Probabilistic Inference System (that implements a probabilistic inference algorithm).
• Example(s):
  • Bayesian Inferencing.
• See: Probabilistic Reasoning, MAP Inference, Cutting Plane Inference.

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References

2014

• http://deepdive.stanford.edu/inference
  • QUOTE: Probabilistic inference is the task of deriving the probability of one or more random variables taking a specific value or set of values. For example, a Bernoulli (Boolean) random variable may describe the event that John has cancer. Such a variable could take a value of 1 (John has cancer) or 0 (John does not have cancer). DeepDive uses probabilistic inference to estimate the probability that the random variable takes value 1: a probability of 0.78 would mean that John is 78% likely to have cancer.

1993

• (Neal, 1993) ⇒ Radford M. Neal. (1993). “Probabilistic Inference Using Markov Chain Monte Carlo Methods." Department of Computer Science, University of Toronto Toronto, CA.

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