• BNT

  • Referenced in 71 articles [sw07384]
  • nodes (probability distributions), exact and approximate inference, parameter and structure learning, and static and dynamic...
  • RStan

  • Referenced in 58 articles [sw13990]
  • Chain Monte Carlo, rough Bayesian inference via variational approximation, and (optionally penalized) maximum likelihood estimation...
  • LibDAI

  • Referenced in 15 articles [sw06422]
  • open source C++ library for discrete approximate inference in graphical models This paper describes ... provides implementations of various exact and approximate inference methods for graphical models with discrete-valued ... fields and factor graphs). It offers various approximations of the partition sum, marginal probability distributions ... other open source software packages for approximate inference is given. libDAI is licensed under...
  • ADVI

  • Referenced in 26 articles [sw34040]
  • inference is a scalable technique for approximate Bayesian inference. Deriving variational inference algorithms requires tedious...
  • trueskill

  • Referenced in 24 articles [sw12352]
  • Bayesian skill rating system with inference by approximate message passing on a factor graph. Used...
  • rstan

  • Referenced in 28 articles [sw16103]
  • Chain Monte Carlo, rough Bayesian inference via variational approximation, and (optionally penalized) maximum likelihood estimation...
  • PILCO

  • Referenced in 20 articles [sw34813]
  • probabilistic modeling of the dynamics and approximate Bayesian inference for policy evaluation and improvement...
  • abcrf

  • Referenced in 12 articles [sw21308]
  • random forests for Bayesian parameter inference. Approximate Bayesian computation (ABC) has grown into a standard...
  • GPstuff

  • Referenced in 23 articles [sw12867]
  • tools include, among others, various inference methods, sparse approximations and model assessment methods. The GPstuff...
  • BayesLogit

  • Referenced in 44 articles [sw09312]
  • methods for posterior inference that (1) circumvent the need for analytic approximations, numerical integration...
  • MCINTYRE

  • Referenced in 8 articles [sw22925]
  • concentrate on the problem of approximate inference in probabilistic logic programming languages based ... distribution semantics. A successful approximate approach is based on Monte Carlo sampling, that consists ... propose an approach for Monte Carlo inference that is based on a program transformation that...
  • TrueSkill

  • Referenced in 21 articles [sw21717]
  • individual skills from team results. Inference is performed by approximate message passing on a factor...
  • Perracotta

  • Referenced in 7 articles [sw12087]
  • introduce solutions that enable a dynamic inference technique to scale to large programs and work ... industrial scenarios. We describe our approximate inference algorithm, present and evaluate heuristics for winnowing...
  • FastInf

  • Referenced in 4 articles [sw06423]
  • FastInf: an efficient approximate inference library The FastInf C++ library is designed to perform memory ... time efficient approximate inference in large-scale discrete undirected graphical models. The focus ... library is propagation based approximate inference methods, ranging from the basic loopy belief propagation algorithm...
  • ProbLog

  • Referenced in 85 articles [sw06945]
  • given query, either exactly or using various approximate methods. ProbLog1 also supports parameter learning ... interpretations setting. ProbLog1 also supports decision-theoretic inference. ProbLog2 allows the user to compute marginal...
  • CTBN-RLE

  • Referenced in 5 articles [sw12961]
  • inference and Gibbs and importance sampling approximate inference for any type of evidence pattern. Additionally...
  • GPyTorch

  • Referenced in 8 articles [sw35483]
  • inference from O(n3) to O(n2). Adapting this algorithm to scalable approximations and complex ... dramatically accelerate both exact GP inference and scalable approximations. Additionally, we provide GPyTorch, a software...
  • GPflow

  • Referenced in 14 articles [sw21518]
  • that it uses variational inference as the primary approximation method, provides concise code through...
  • FastTree

  • Referenced in 7 articles [sw28979]
  • instead of a Distance Matrix. FastTree infers approximately-maximum-likelihood phylogenetic trees from alignments...
  • epiABC

  • Referenced in 9 articles [sw23334]
  • stochastic epidemic models using approximate Bayesian computation. Likelihood-based inference for disease outbreak data ... incomplete. In this paper we review recent Approximate Bayesian Computation (ABC) methods for the analysis...