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We introduce partial Markov categories.
Newcomb’s Problem and Two Principles of Choice
Robert Nozick · 1969
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Categories for the Working Mathematician
Saunders Mac Lane · 1971
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Coalgebras and Cartesian Categories
Thomas Fox · 1976
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Counterfactuals and two kinds of expected utility
Allan Gibbard and William L. Harper · 1978
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Causal decision theory
David Lewis · 1981
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Jeffrey’s rule of conditioning
Glenn Shafer · 1981
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Michèle Giry · 1982
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Bicategories of partial maps
Aurelio Carboni · 1987
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Dominical categories: recursion theory without elements1 2
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Decision theory in expert systems and artificial intelligence
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Probabilistic reasoning in intelligent systems: networks of plausible inference
Judea Pearl · 1988
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Categories of partial maps
Edmund Robinson and Giuseppe Rosolini · 1988
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The logic of decision
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Judea Pearl · 1990
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The geometry of tensor calculus, i
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Models of sharing graphs: a categorical semantics of let and letrec
Masahito Hasegawa · 1997
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An Algebraic Presentation of Term Graphs, via GS-Monoidal Categories
Andrea Corradini and Fabio Gadducci · 1999
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The foundations of causal decision theory
James M Joyce · 1999
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The Category of Markov Kernels
Prakash Panangaden · 1999
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Restriction categories I: categories of partial maps
J. Robin B. Cockett and Stephen Lack · 2002
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Restriction categories ii: partial map classification
J. Robin B. Cockett and Stephen Lack · 2003
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A history of Haskell: being lazy with class
Paul Hudak, John Hughes, Simon L. Peyton Jones, and Philip Wadler · 2007
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Causality
Judea Pearl · 2009
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Fredrik Dahlqvist and Dexter Kozen · 2019
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A probability monad as the colimit of spaces of finite samples
Tobias Fritz and Paolo Perrone · 2019
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Picturing classical and quantum bayesian inference
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A domain theory for statistical probabilistic programming
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The logical essentials of bayesian reasoning
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Functorial semantics for partial theories
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Free GS-monoidal categories and free Markov categories
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