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 ...
The Virtual Brain Inference (VBI) toolkit enables efficient, accurate, and scalable Bayesian inference over whole-brain network models, improving parameter estimation, uncertainty quantification, and ...
Probabilistic Sentential Decision Diagrams (PSDDs) are an elegant framework for learning from and reasoning about data. They provide tractable representations of discrete probability distributions ...
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