Probabilistic model checking and Markov decision processes (MDPs) form two interlinked branches of formal analysis for systems operating under uncertainty. These techniques offer a mathematical ...

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 ...

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 ...