A probabilistic powerdomain of evaluations
Proceedings of the Fourth Annual Symposium on Logic in computer science
Probabilistic predicate transformers
ACM Transactions on Programming Languages and Systems (TOPLAS)
Stochastic lambda calculus and monads of probability distributions
POPL '02 Proceedings of the 29th ACM SIGPLAN-SIGACT symposium on Principles of programming languages
A probabilistic language based upon sampling functions
Proceedings of the 32nd ACM SIGPLAN-SIGACT symposium on Principles of programming languages
Data Analysis and Graphics Using R: An Example-based Approach (Cambridge Series in Statistical and Probabilistic Mathematics)
Probabilistic modelling, inference and learning using logical theories
Annals of Mathematics and Artificial Intelligence
Varying Domain Representations in Hagl
DSL '09 Proceedings of the IFIP TC 2 Working Conference on Domain-Specific Languages
A DSL for Explaining Probabilistic Reasoning
DSL '09 Proceedings of the IFIP TC 2 Working Conference on Domain-Specific Languages
Embedded Probabilistic Programming
DSL '09 Proceedings of the IFIP TC 2 Working Conference on Domain-Specific Languages
Measure transformer semantics for Bayesian machine learning
ESOP'11/ETAPS'11 Proceedings of the 20th European conference on Programming languages and systems: part of the joint European conferences on theory and practice of software
Just do it: simple monadic equational reasoning
Proceedings of the 16th ACM SIGPLAN international conference on Functional programming
Modeling genome evolution with a DSEL for probabilistic programming
PADL'06 Proceedings of the 8th international conference on Practical Aspects of Declarative Languages
A type theory for probability density functions
POPL '12 Proceedings of the 39th annual ACM SIGPLAN-SIGACT symposium on Principles of programming languages
SLE'11 Proceedings of the 4th international conference on Software Language Engineering
Functional high performance financial IT: the hiperfit research center in copenhagen
TFP'11 Proceedings of the 12th international conference on Trends in Functional Programming
Dynamic symbolic computation for domain-specific language implementation
LOPSTR'11 Proceedings of the 21st international conference on Logic-Based Program Synthesis and Transformation
An embedded DSL for stochastic processes: research article
Proceedings of the 1st ACM SIGPLAN workshop on Functional high-performance computing
Elementary probability theory in the eindhoven style
MPC'12 Proceedings of the 11th international conference on Mathematics of Program Construction
Typed linear algebra for weigthed (probabilistic) automata
CIAA'12 Proceedings of the 17th international conference on Implementation and Application of Automata
A model-learner pattern for bayesian reasoning
POPL '13 Proceedings of the 40th annual ACM SIGPLAN-SIGACT symposium on Principles of programming languages
A visual language for explaining probabilistic reasoning
Journal of Visual Languages and Computing
What are the Odds?: probabilistic programming in Scala
Proceedings of the 4th Workshop on Scala
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At the heart of functional programming rests the principle of referential transparency, which in particular means that a function f applied to a value x always yields one and the same value y=f(x). This principle seems to be violated when contemplating the use of functions to describe probabilistic events, such as rolling a die: It is not clear at all what exactly the outcome will be, and neither is it guaranteed that the same value will be produced repeatedly. However, these two seemingly incompatible notions can be reconciled if probabilistic values are encapsulated in a data type.