• ADVI

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

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

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

  • Referenced in 11 articles [sw21308]
  • Approximate Bayesian computation (ABC) has grown into a standard methodology that manages Bayesian inference...
  • rstan

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

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

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

  • Referenced in 8 articles [sw21021]
  • v2.0: a software to make approximate Bayesian computation inferences about population history using single nucleotide ... comprehensive analysis of population history using approximate Bayesian computation on DNA polymorphism data. Version...
  • AABC

  • Referenced in 6 articles [sw16116]
  • sets is computationally infeasible. Approximate Bayesian computation (ABC) methods perform inference on model-specific parameters ... sampled by ABC, inference is not straightforward. We present approximate approximate Bayesian computation” (AABC ... class of methods that extends simulation-based inference by ABC to models in which simulating ... inform a non-mechanistic statistical model that approximates the correct parametric model and enables efficient...
  • spectralGP

  • Referenced in 14 articles [sw08081]
  • Approximate Gaussian processes using the Fourier basis. Routines for creating, manipulating, and performing Bayesian inference...
  • LibDAI

  • Referenced in 15 articles [sw06422]
  • provides implementations of various exact and approximate inference methods for graphical models with discrete-valued ... variables. libDAI supports directed graphical models (Bayesian networks) as well as undirected ones (Markov random ... 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...
  • choix

  • Referenced in 2 articles [sw26417]
  • Choice Model. choix makes it easy to infer model parameters from these different types ... Spectral Ranking; Minorization-Maximization; Rank Centrality; Approximate Bayesian inference with expectation propagation...
  • BayesLogit

  • Referenced in 44 articles [sw09312]
  • data-augmentation strategy for fully Bayesian inference in models with binomial likelihoods. The approach appeals ... methods for posterior inference that (1) circumvent the need for analytic approximations, numerical integration...
  • ABC-SysBio

  • Referenced in 6 articles [sw24739]
  • SysBio: Approximate Bayesian Computation in Python with GPU support. MOTIVATION: The growing field of systems ... number of statistical approaches, both frequentist and Bayesian, have been proposed to answer these questions ... implements parameter inference and model selection for dynamical systems in an approximate Bayesian computation ... rejection sampler, ABC SMC for parameter inference and ABC SMC for model selection...
  • DR-ABC

  • Referenced in 3 articles [sw24742]
  • Approximate Bayesian Computation with Kernel-Based Distribution Regression. Performing exact posterior inference in complex generative ... intractable likelihood function. Approximate Bayesian computation (ABC) is an inference framework that constructs an approximation...
  • cosmoabc

  • Referenced in 3 articles [sw20219]
  • cosmoabc: Likelihood-free inference via Population Monte Carlo Approximate Bayesian Computation. Approximate Bayesian Computation...
  • BFDA

  • Referenced in 2 articles [sw14769]
  • covariance function. An option of approximating the Bayesian inference process with cubic B-spline basis...
  • queuecomputer

  • Referenced in 2 articles [sw19185]
  • proceed with parameter inference from data. Approximate Bayesian computation could offer a straight-forward...
  • TrueSkill

  • Referenced in 21 articles [sw21717]
  • skill rating system. We present a new Bayesian skill rating system which can be viewed ... infer individual skills from team results. Inference is performed by approximate message passing...
  • OUOUCIR

  • Referenced in 1 article [sw34465]
  • using Cox-Ingersoll-Ross process: an approximate Bayesian computation approach. Over the past decades, Gaussian ... algorithm for parameter estimation and inference under Approximate Bayesian Computation (ABC) is proposed. Simulation studies...