• DACE

  • Referenced in 188 articles [sw04715]
  • this approximation model as a surrogate for the computer model. The software also addresses...
  • DAKOTA

  • Referenced in 77 articles [sw05202]
  • components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization...
  • ParEGO

  • Referenced in 68 articles [sw10968]
  • latin hypercube and updates a Gaussian processes surrogate model of the search landscape after every...
  • SUMO

  • Referenced in 26 articles [sw12763]
  • Surrogate Modeling Toolbox (SUMO Toolbox) is a Matlab toolbox that automatically builds accurate surrogate models...
  • SURROGATES

  • Referenced in 16 articles [sw07575]
  • SURROGATES Toolbox is a general-purpose MATLAB library of multidimensional function approximation and optimization methods ... hypercube design, D-optimal and maxmin designs. Surrogates: kriging, polynomial response surface, radial basis neural ... error; root mean square error; and others). Surrogate-based optimization: efficient global optimization (EGO) algorithm ... Other capabilities: global sensitivity analysis and conservative surrogates via safety margin...
  • GPS-ABC

  • Referenced in 18 articles [sw16117]
  • Gaussian Process Surrogate Approximate Bayesian Computation. Scientists often express their understanding of the world through ... Gaussian process which acts as a surrogate function for the simulated statistics. Experiments...
  • MISO

  • Referenced in 13 articles [sw20541]
  • MISO: mixed-integer surrogate optimization framework. We introduce MISO, the mixed-integer surrogate optimization framework ... function evaluations. Therefore, we use computationally cheap surrogate models to approximate the expensive objective function ... should be evaluated. We develop a general surrogate model framework and show how sampling strategies ... well-known surrogate model algorithms for continuous optimization can be modified for mixed-integer variables...
  • SO-I

  • Referenced in 15 articles [sw10100]
  • surrogate model algorithm for expensive nonlinear integer programming problems including global optimization applications. This paper ... presents the surrogate model based algorithm SO-I for solving purely integer optimization problems that...
  • PAINT

  • Referenced in 12 articles [sw10390]
  • PAINT method implies a mixed integer linear surrogate problem for the original problem which ... synchronous NIMBUS method), the scalarizations of the surrogate problem can be optimized with available mixed ... interactive method is fast with the surrogate problem even though the problem is computationally expensive...
  • FIVER

  • Referenced in 19 articles [sw18341]
  • include: (a) the definition of a discrete surrogate material interface, (b) the computation...
  • ooDACE

  • Referenced in 10 articles [sw12876]
  • analyzing data from computationally expensive simulation codes, surrogate modeling methods are firmly established as facilitators ... visualization and optimization. Kriging is a popular surrogate modeling technique used for the Design...
  • Surrogate

  • Referenced in 6 articles [sw16061]
  • package Surrogate. In a clinical trial, it frequently occurs that the most credible outcome ... treatment effect on the true endpoint (a surrogate endpoint). The package ’Surrogate’ allows ... evaluation of the appropriateness of a candidate surrogate endpoint based on the meta-analytic, information...
  • sva

  • Referenced in 6 articles [sw21306]
  • package SVA: Surrogate Variable Analysis. The sva package contains functions for removing batch effects ... contains functions for the identifying and building surrogate variables for high-dimensional data sets. Surrogate ... three ways: (1) identifying and estimating surrogate variables for unknown sources of variation in high ... biorXiv). Removing batch effects and using surrogate variables in differential expression analysis have been shown...
  • pyunicorn

  • Referenced in 8 articles [sw19314]
  • interacting networks, node-weighted statistics or network surrogates. Additionally, pyunicorn provides insights into the nonlinear ... recurrence networks, visibility graphs and construction of surrogate time series. The range of possible applications...
  • RAMP

  • Referenced in 10 articles [sw02493]
  • both levels, based on Lagrangean and surrogate constraint relaxation on the dual side...
  • Multsurr

  • Referenced in 5 articles [sw37141]
  • Regression calibration for logistic regression with multiple surrogates for one exposure. Methods have been developed ... approaches typically assume that there is one surrogate for each exposure. Occupational exposures are quite ... area. In this setting, there are several surrogates which are used to define an individual ... exposure measurement error from multiple surrogates. The health outcome is assumed to be binary...
  • mlrMBO

  • Referenced in 9 articles [sw19214]
  • approximating the given objective function through a surrogate regression model. It is designed for both...
  • ARGONAUT

  • Referenced in 9 articles [sw20651]
  • sampling techniques, in order to develop accurate surrogate representations of unknown equations, which are globally...
  • MATSuMoTo

  • Referenced in 4 articles [sw20551]
  • MATSuMoTo: The MATLAB surrogate model toolbox for computationally expensive black-box global optimization problems. MATSuMoTo ... MATLAB Surrogate Model Toolbox for computationally expensive, black-box, global optimization problems that may have ... objective function, derivatives are not available. Hence, surrogate models are used as computationally cheap approximations ... these challenges. MATSuMoTo offers various choices for surrogate models and surrogate model mixtures, initial experimental...
  • RBFOpt

  • Referenced in 8 articles [sw28416]
  • which builds and iteratively refines a surrogate model of the unknown objective function...