The key idea behind the probabilistic framework to machine learning is that learning can be thought of as inferring plausible models to explain observed data. A machine can use such models to make ...

We live in a world where a lot of things seem to happen by pure chance, from winning the Lotto to losing your car keys. But the truth is, the likelihood of many everyday things happening is heavily ...

Bayesian Networks, also known as Belief Networks or Bayes Nets, are a powerful probabilistic graphical model used for reasoning under uncertainty. They have been successfully applied to a wide range ...

Continuous learning in artificial intelligence involves a delicate trade-off between forgetting old knowledge and rigidity in ...

When our brains don't have a good intuition for reasoning with numbers, explicit probabilistic thinking can lead to improved decision-making. A man went on an airplane ride. Unfortunately, he fell out ...

SCIENCE, being a human activity, is not immune to fashion. For example, one of the first mathematicians to study the subject of probability theory was an English clergyman called Thomas Bayes, who was ...

Evidence can modify our beliefs, but the impact it has depends upon those beliefs. An 18th century priest has something to say about that, in what could be seen as a mathematical formulation of the ...