Name
Abstract | ||
|---|---|---|
Reasoning with probabilistic models is a widespread and successful technique in areas ranging from computer vi- sion, to natural language processing, to bioinformatics. Currently, these reasoning systems are either coded from scratch in general-purpose languages or use formalisms such as Bayesian networks that have limited expressive power. In both cases, the resulting systems are difcult to mod- ify, maintain, compose, and interoperate with. This work presents Probabilistic Scheme, an embedding of probabilis- tic computation into Scheme. This gives programmers an expressive language for implementing modular probabilistic models that integrate naturally with the rest of Scheme. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1145/1297081.1297085 | dynamic languages symposium |
Keywords | Field | DocType |
general-purpose language,bayesian network,natural language processing,reasoning system,expressive power,probabilistic language scheme,probabilistic scheme,probabilistic model,probabilistic computation,scheme,expressive language,probability,embedding,modular probabilistic model | Divergence-from-randomness model,Programming language,Interoperability,Computer science,Probabilistic CTL,Theoretical computer science,Bayesian network,Probabilistic logic,Modular design,Probabilistic argumentation,Rotation formalisms in three dimensions | Conference |
Citations | PageRank | References |
10 | 2.22 | 8 |
Authors | ||
1 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alexey Radul | 1 | 35 | 8.90 |