Most probabilistic programming languages for Bayesian inference give either operational semantics in terms of sampling, or denotational semantics in terms of measure-theoretic distributions. It is important that we can relate the two, given that practitioners often reason both analytically (e.g., density) as well as algorithmically (i.e., in terms of sampling) about distributions. In this paper...

We introduce the first, general purpose, slice sampling inference engine for probabilistic programs. This engine is released as part of StocPy, a new Turing-Complete probabilistic programming language, available as a Python library. We present a transdimensional generalisation of slice sampling which is necessary for the inference engine to work on traces with different numbers of random variab...

This paper presents a shallow embedding of a probabilistic functional programming language in higher order logic. The language features monadic sequencing, recursion, random sampling, failures and failure handling, and black-box access to oracles. Oracles are probabilistic functions which maintain hidden state between different invocations. To that end, we propose generative probabilistic syste...

introduction: in early typical language development, children understand words before they are able to use them in speech. children with autism spectrum disorders (asd) generally show impairments in both the comprehension and the production of language. however, the relative degree of delay or impairment in each of these sub-domains may also be atypical and remains less well-understood. materia...

Stochastic filtering is the problem of estimating the state of a dynamic system after time passes and given partial observations. It is fundamental to automatic tracking, planning, and control of real-world stochastic systems such as robots, programs, and autonomous agents. This paper presents a novel sampling-based filtering algorithm. Its expected error is smaller than sequential Monte Carlo ...

in the present research. the relationship of social and language development of 1 grade girl students has been investigated. with the aim of showing the interrelatedness of these variables and the significant effect of social development on language development. thirty 1si grade girl students were selected through stratified random sampling. results from the administration of told-p-3 and weinl...

BACKGROUND This study evaluates the metric and scalar invariance of the Sport Anxiety Scale-2 (SAS-2), which is considered one of the best sport performance anxiety assessment tools for child and adolescent athletes, across four sampling variables: language, gender, age and type of sport. METHOD The participants were 842 athletes (Mage = 11.73, SD = 2.20) from Spain, Belgium and Portugal, eac...

A chromium electroplating bath with the ability to produce homogenous mist was used to evaluate parameters influencing hexavalent chromium (Cr+6) mist sampling methods. The results of 48 Cr+6mist samples collected using the U.S. National Institute for Occupational Safety and Health method 7600...

If the dataset available to machine learning results from cluster sampling (e.g. patients from a sample of hospital wards), the usual cross-validation error rate estimate can lead to biased and misleading results. An adapted cross-validation is described for this case. Using a simulation, the sampling distribution of the generalization error rate estimate, under cluster or simple random samplin...