The past decade has witnessed significant advances in causal inference and Bayesian network learning, two intertwined disciplines that allow researchers to discern underlying cause‐and‐effect ...
For decades, artificial intelligence has excelled at spotting patterns in data. Machine learning models can predict customer behavior, forecast market trends, or identify medical risks with high ...
The Annals of Applied Statistics, Vol. 12, No. 4 (December 2018), pp. 2517-2539 (23 pages) Government agencies offer economic incentives to citizens for conservation actions, such as rebates for ...
On Thursday the 21st of November 2019, M.Sc. Topi Talvitie will defend his doctoral thesis on Counting and Sampling Directed Acyclic Graphs for Learning Bayesian Networks. The thesis is a part of ...
Causal inference with observational data frequently relies on the notion of the propensity score (PS) to adjust treatment comparisons for observed confounding factors. As decisions in the era of "big ...
Artificial intelligence owes a lot of its smarts to Judea Pearl. In the 1980s he led efforts that allowed machines to reason probabilistically. Now he’s one of the field’s sharpest critics. In his ...
Norman Fenton is a Director of Agena Ltd, a company that specialises in risk management for critical systems using Bayesian networks. He also currently receives funding from the EPSRC under project EP ...
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