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Eberhardt, Frederick - Philosophy-Neuroscience-Psychology Program & Department of Philosophy, Washington University in St. Louis
Causation and Intervention Frederick Eberhardt
Running Head: Reliability via Synthetic A Priori Reliability via Synthetic A Priori
HISTORY & PHILOSOPHY OF SCIENCE & MEDICINE SEMINAR SERIES Spring, 2009
INFORMATION SOCIETY TECHNOLOGIES Project IST-2001-33562 MoWGLI
Combining Experiments to Discover Linear Cyclic Models with Latent Variables
Sufficient Condition for Pooling Data from different Distributions Frederick Eberhardt fde@cmu.edu
Journal of Machine Learning Research 1 (2008) 1-10 Submitted 12/08; Published Causal Discovery as a Game
Noisy-OR Models with Latent Confounding Antti Hyttinen
Confirmation in the Cognitive Sciences: The Problematic Case of Bayesian Models
Interventions and Causal Inference Frederick Eberhardt1
Almost Optimal Intervention Sets for Causal Discovery Frederick Eberhardt
Introduction to the Epistemology of Causation Frederick Eberhardt
On the Number of Experiments Sufficient and in the Worst Case Necessary to Identify All Causal Relations Among N Variables
Compact Similarity Joins Brent Bryan #1
Causal discovery for linear cyclic models with latent variables Antti Hyttinen1, Frederick Eberhardt2, and Patrik O. Hoyer1,3
N-1 Experiments Suffice to Determine the Causal Relations Among N Variables Frederick Eberhardt
