Foundations for Bayesian networks (2001)

by Jon Williamson , David Corfield , Jon Williamson
Citations:11 - 7 self

Active Bibliography

§2 Categorising Philosophical Theories of Causality 2 §3 Probabilistic Theories of Causality 3 – Jon Williamson - 2009
2 A Probability Index of the Robustness of a Causal Inference – Wei Pan, Kenneth A. Frank
4 Machine Learning and the Philosophy of Science: a Dynamic Interaction – Jon Williamson - 2001
3 A dynamic interaction between machine learning and the philosophy of science – Jon Williamson - 2004
§3 The Complex-Systems Theory §4 General Problems for Mechanistic Causality – Jon Williamson, The Epistemic Theory - 2011
MARIAM THALOS THE REDUCTION OF CAUSAL PROCESSES – unknown authors
Recommended Citation – Frederick Eberhardt, Richard Scheines, Frederick Eberhardt, Richard Scheines
208 A Theory Of Inferred Causation – Judea Pearl, T.S. Verma - 1991
Introduction – Federica Russo, Jon Williamson
32 An Extended Class of Instrumental Variables for the Estimation of Causal Effects – Karim Chalak, Halbert White - 1996
7 Generic versus single-case causality: the case of autopsy. European Journal for Philosophy of Science, forthcoming – Federica Russo, Jon Williamson - 2011
1 Understanding of what engineers “do – Jon Williamson, Julian Reiss, Jon Williamson - 2002
Editor: Julian ReissLearning Causal Relationships – Jon Williamson, Jon Williamson
5 of LaborOn the Role of Counterfactuals in Inferring Causal Effects of Treatments – Jochen Kluve, Jochen Kluve
Computation and Causation * – Richard Scheines
1 Ecology Model – Sabrina E. Russo, Susan K, David A. Coomes
8 Evolutionary Theory and the Reality of Macro Probabilities – Elliott Sober
1 A Criterion of Probabilistic Causality – Charles R. Twardy, Kevin B. Korb, Michaelis Michael, Lucas Hope
Does a Cause Increase the Probability of Its Effects? – Jon Williamson - 1999