Results 1 to 10 of about 135,499 (155)
Approximate Bayesian Computation for Discrete Spaces [PDF]
Entropy, 2021 Many real-life processes are black-box problems, i.e., the internal workings are inaccessible or a closed-form mathematical expression of the likelihood function cannot be defined.
Ilze A. Auzina, Jakub M. Tomczak
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Approximate Bayesian Computation Via the Energy Statistic [PDF]
IEEE Access, 2020 Approximate Bayesian computation (ABC) has become an essential part of the Bayesian toolbox for addressing problems in which the likelihood is prohibitively expensive or entirely unknown, making it intractable. ABC defines a pseudo-posterior by comparing
Hien Duy Nguyen +3 more
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Approximate Bayesian computation.
PLoS Computational Biology, 2013 Approximate Bayesian computation (ABC) constitutes a class of computational methods rooted in Bayesian statistics. In all model-based statistical inference, the likelihood function is of central importance, since it expresses the probability of the ...
Mikael Sunnåker +5 more
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ABCDP: Approximate Bayesian Computation with Differential Privacy [PDF]
Entropy, 2021 We developed a novel approximate Bayesian computation (ABC) framework, ABCDP, which produces differentially private (DP) and approximate posterior samples.
Mijung Park +2 more
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Approximate Bayesian Computation by Subset Simulation [PDF]
SIAM Journal on Scientific Computing, 2014 A new Approximate Bayesian Computation (ABC) algorithm for Bayesian updating of model parameters is proposed in this paper, which combines the ABC principles with the technique of Subset Simulation for efficient rare-event simulation, first developed in ...
Beck, James L. +3 more
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A wall-time minimizing parallelization strategy for approximate Bayesian computation. [PDF]
PLoS ONEApproximate Bayesian Computation (ABC) is a widely applicable and popular approach to estimating unknown parameters of mechanistic models. As ABC analyses are computationally expensive, parallelization on high-performance infrastructure is often ...
Emad Alamoudi +6 more
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New insights into Approximate Bayesian Computation [PDF]
Annales de l'Institut Henri Poincaré, Probabilités et Statistiques, 2015 International audienceApproximate Bayesian Computation (ABC for short) is a family of computational techniques which offer an almost automated solution in situations where evaluation of the posterior likelihood is computationally prohibitive, or whenever
Biau, Gérard +2 more
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Approximate Bayesian Computation for Copula Estimation
Statistica, 2015 We describe a simple method for making inference on a functional of a multivariate distribution. The method is based on a copula representation of the multivariate distribution and it is based on the properties of an Approximate Bayesian Monte\,Carlo ...
Clara Grazian, Brunero Liseo
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Accounting for contact network uncertainty in epidemic inferences with Approximate Bayesian Computation [PDF]
Applied Network ScienceIn models of infectious disease dynamics, the incorporation of contact network information allows for the capture of the non-randomness and heterogeneity of realistic contact patterns.
Maxwell H. Wang, Jukka-Pekka Onnela
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Dynamic calibration with approximate Bayesian computation for a microsimulation of disease spread [PDF]
Scientific Reports, 2023 The global COVID-19 pandemic brought considerable public and policy attention to the field of infectious disease modelling. A major hurdle that modellers must overcome, particularly when models are used to develop policy, is quantifying the uncertainty ...
Molly Asher +4 more
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