Probabilistic graphical models form a unifying framework for representing complex multivariate distributions and reasoning about causality. At their core, these models employ graphs in which nodes ...

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 ...

Over the past two decades, new technologies have helped scientists generate a vast amount of biological data. Large-scale experiments in genomics, transcriptomics, proteomics, and cytometry can ...