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4
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Machine Learning and the Philosophy of Science: a Dynamic Interaction
– Jon Williamson
- 2001
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3
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A dynamic interaction between machine learning and the philosophy of science
– Jon Williamson
- 2004
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1
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A Probability Index of the Robustness of a Causal Inference
– Wei Pan, Kenneth A. Frank
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175
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A Theory Of Inferred Causation
– Judea Pearl, T.S. Verma
- 1991
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Introduction
– Federica Russo, Jon Williamson
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21
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An Extended Class of Instrumental Variables for the Estimation of Causal Effects
– Karim Chalak, Halbert White
- 1996
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2
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Generic versus single-case causality: the case of autopsy. European Journal for Philosophy of Science, forthcoming
– Federica Russo, Jon Williamson
- 2011
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1
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Understanding of what engineers “do
– Jon Williamson, Julian Reiss, Jon Williamson
- 2002
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1
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Ecology Model
– Sabrina E. Russo, Susan K, David A. Coomes
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4
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Evolutionary Theory and the Reality of Macro Probabilities
– Elliott Sober
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1
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A Criterion of Probabilistic Causality
– Charles R. Twardy, Kevin B. Korb, Michaelis Michael, Lucas Hope
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Does a Cause Increase the Probability of Its Effects?
– Jon Williamson
- 1999
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Lawn
– Dr. Kevin Korb, Charles Twardy (monash Csse, Causal Models
- 2004
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95
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A theory of causal learning in children: Causal maps and Bayes nets
– Alison Gopnik, Clark Glymour, David M. Sobel, Laura E. Schulz, Tamar Kushnir, David Danks
- 2004
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3
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A Unified Framework for Defining and Identifying Causal Effects
– Halbert White, Karim Chalak
- 2006
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3
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Parametric and Nonparametric Estimation of Covariate-Conditioned Average Effects
– Halbert White, Karim Chalak
- 2005
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3
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Models of Scientific Explanation
– Paul Thagard, Abninder Litt, The Cambridge
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A manifesto
– Phyllis Mckay Illari, Federica Russo, Jon Williamson
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Coincidences and How to Think about Them
– Elliott Sober
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