Bayesian nonparametric mixture models represent a powerful statistical framework that extends traditional mixture modelling by allowing the number of mixture components to be inferred from the data ...

For humans and machines, intelligence requires making sense of the world — inferring simple explanations for the mishmosh of information coming in through our senses, discovering regularities and ...

Some say that if you can’t measure something, you’re not doing science. Bayesian logic offers a way to measure things that were previously unmeasurable, allowing us to test hypotheses and predictions ...

We suspect that you had more than enough mathematics in the form of Bayes Theorem last week so this week we’ll explain how it’s used in what is called Bayesian filtering to remove spam (note that the ...

We analyse the performance of a recursive Monte Carlo method for the Bayesian estimation of the static parameters of a discrete-time state-space Markov model. The algorithm employs two layers of ...

What Is A Probabilistic Model? A probabilistic model is a statistical tool that accounts for randomness or uncertainty when predicting future events. Instead of giving a definitive answer, it ...