Probabilistic graphical models are a powerful technique for handling uncertainty in machine learning. The course will cover how probability distributions can be represented in graphical models, how ...

A recent announcement appearing in MIT News, “Machine learning branches out,” highlights new research in probabilistic graphical models. In a paper being presented in December at the annual conference ...

The Uncertainty Engine is guiding research in fusion plasma physics. Could similar approaches benefit fission research as well?

Bayesian networks, also known as Bayes nets, belief networks, or decision networks, are a powerful tool for understanding and reasoning about complex systems under uncertainty. They are essentially ...

In systems that exhibit artificial intelligence (AI), an agent at its centre has to learn and represent a model of its environment, reason about it, and decide on its actions. A possible approach to ...

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 ...