Bayesian inference provides a robust framework for combining prior knowledge with new evidence to update beliefs about uncertain quantities. In the context of statistical inverse problems, this ...

The US Food and Drug Administration (FDA) is now “open to bayesian statistics,” contrasting this with the frequentist approach that the agency and the drug industry have historically relied on for ...

The basic idea of Q-learning is that 'the value of a certain state (Q value) is determined by the reward obtained and the value of the state at the next point in time', and is expressed by the ...

Articulate the primary interpretations of probability theory and the role these interpretations play in Bayesian inference Use Bayesian inference to solve real-world statistics and data science ...

This course introduces the theoretical, philosophical, and mathematical foundations of Bayesian Statistical inference. Students will learn to apply this foundational knowledge to real-world data ...

Dr. Karl Friston, a distinguished psychiatrist, neuroscientist, and pioneer of modern neuroimaging, is a leading expert on intelligence, both natural and artificial. I've followed his work with ...

This course is available on the MSc in Applied Social Data Science, MSc in Data Science, MSc in Econometrics and Mathematical Economics, MSc in Health Data Science, MSc in Operations Research & ...