Sökning: "Probabilistic programming languages"

Hittade 5 avhandlingar innehållade orden Probabilistic programming languages.

  1. 1. Correct and Efficient Monte Carlo Inference for Universal Probabilistic Programming Languages

    Författare :Daniel Lundén; David Broman; Lawrence Murray; Joakim Jaldén; Sam Staton; KTH; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Probabilistic programming languages; Compilers; Static program analysis; Monte Carlo inference; Operational semantics; Probabilistiska programmeringsspråk; Kompilatorer; Statisk programanalys; Monte Carlo-inferens; Operationell semantik; Informations- och kommunikationsteknik; Information and Communication Technology;

    Sammanfattning : Probabilistic programming languages (PPLs) allow users to express statistical inference problems that the PPL implementation then, ideally, solves automatically. In particular, PPL users can focus on encoding their inference problems, and need not concern themselves with the intricacies of inference. LÄS MER

  3. 2. Probabilistic Programming for Birth-Death Models of Evolution

    Författare :Jan Kudlicka; Johannes Borgström; Thomas B. Schön; Lawrence M. Murray; Bret Larget; Uppsala universitet; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; probabilistic programming; birth-death models; statistical phylogenetics; particle filters; sequential Monte Carlo SMC ; Computer Science; Datavetenskap;

    Sammanfattning : Phylogenetic birth-death models constitute a family of generative models of evolution. In these models an evolutionary process starts with a single species at a certain time in the past, and the speciations—splitting one species into two descendant species—and extinctions are modeled as events of non-homogenous Poisson processes. LÄS MER

  4. 3. Towards Correct and Efficient Program Execution in Decentralized Networks: Programming Languages, Semantics, and Resource Management

    Författare :Karl Palmskog; Mads Dam; Rocco De Nicola; KTH; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; distributed objects; decentralization; implementation correctness; network protocols; object mobility; Computer Science; Datalogi;

    Sammanfattning : The Internet as of 2014 connects billions of devices, and is expected to connect tens of billions by 2020. To meet escalating requirements, networks must be scalable, easy to manage, and be able to efficiently execute programs and disseminate data. The prevailing use of centralized systems and control in, e.g. LÄS MER

  5. 4. Reliable Uncertainty Quantification in Statistical Learning

    Författare :David Widmann; Fredrik Lindsten; Dave Zachariah; Erik Sjöblom; Dino Sejdinovic; Uppsala universitet; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Reliability; Calibration; Uncertainty; Probabilistic Model; Prediction; Julia; Machine learning; Maskininlärning;

    Sammanfattning : Mathematical models are powerful yet simplified abstractions used to study, explain, and predict the behavior of systems of interest. This thesis is concerned with their latter application as predictive models. LÄS MER

  7. 5. Machine learning using approximate inference : Variational and sequential Monte Carlo methods

    Författare :Christian Andersson Naesseth; Thomas Schön; Fredrik Lindsten; Iain Murray; Linköpings universitet; []
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY;

    Sammanfattning : Automatic decision making and pattern recognition under uncertainty are difficult tasks that are ubiquitous in our everyday life. The systems we design, and technology we develop, requires us to coherently represent and work with uncertainty in data. LÄS MER