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 ...

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 ...

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 ...

Probability underpins AI, cryptography and statistics. However, as the philosopher Bertrand Russell said, “Probability is the most important concept in modern science, especially as nobody has the ...

Trustworthy AI isn’t just about predicting the right outcome; it’s about knowing how confident we should actually be.

The world is full of uncertainty: accidents, storms, unruly financial markets, noisy communications. The world is also full of data. Probabilistic modeling and the related field of statistical ...

Transactions of the Institute of British Geographers is a leading international journal of major research papers. It is one of the most widely read and cited geographical journals. It publishes ...

This study investigates the potential of probabilistic classification to enhance credit-scoring accuracy, with a focus on model validation through reliability thresholds. By quantifying prediction ...

Traders in bonds and credit default swaps are bombarded with information on the default probabilities implied by credit spreads using a simple ratio. This ratio predicts that the credit spread will be ...