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Sep 1, 2023 · In the first half of 2023, the machine learning programs ChatGPT and GPT-4 changed the landscape of artificial intelligence research seemingly overnight. Judea Pearl’s research bridges the subjects of statistics and artificial intelligence and highlights the importance of causality in both settings. Dana Mackenzie, Pearl’s co-author for The Book of Why, interviews him here to get his take ...
[6] Pearl J. Radical empiricism and machine learning research. In Causal analysis in theory and practice (Blog); 2020b July 26. https://ucla.in/32YKcWy [7] Pearl J, Mackenzie D. The book of why: the new science of cause and effect. New York: Basic Books; 2018.
JUDEA PEARL . UCLA Computer Science Department Cognitive Systems Lab 4532 Boelter Hall tel: (310) 825-3243 fax: (310) 825-2273 email: judea@cs.ucla.edu
Aug 31, 2018 · 1. The Book of Why: The New Science of Cause and Effect Judea Pearl and Dana Mackenzie Basic Books, 2018. 429 pp.
Generalized best-first search strategies and the optimality of A. R Dechter, J Pearl. Journal of the ACM (JACM) 32 (3), 505-536. , 1985. 1534. 1985. Reverend Bayes on inference engines: A distributed hierarchical approach. J Pearl. Probabilistic and Causal Inference: The Works of Judea Pearl, 129-138.
Judea Pearl. Judea Pearl (born September 4, 1936) is an Israeli-American computer scientist and philosopher, best known for championing the probabilistic approach to artificial intelligence and the development of Bayesian networks (see the article on belief propagation ). He is also credited for developing a theory of causal and counterfactual ...
Jul 26, 2018 · In this excerpt from The Book of Why, Judea Pearl and Dana Mackenzie explain how the founders of modern statistics “squandered” the chance to establish the science of causal inference. S ome tens of thousands of years ago, humans began to realize that certain things cause other things and that tinkering with the former can change the latter.
