Researchers developed a Bayesian Gated Recurrent Unit architecture that dynamically scales trading capital using uncertainty ...

Scientific modeling faces a tradeoff between the interpretability of mechanistic theory and the predictive power of machine learning. While existing hybrid approaches have made progress by ...

This course provides a rigorous yet practical introduction to Bayesian methods for statistical inference, probabilistic modeling, knowledge representation, and decision-making under uncertainty.

McGill University researchers have developed a more energy-efficient method of building AI systems that are better at ...