The following pages link to EGO (Q19615):
Displaying 50 items.
- One-dimensional modeling of fractional flow reserve in coronary artery disease: uncertainty quantification and Bayesian optimization (Q1988087) (← links)
- Unified uncertainty analysis under probabilistic, evidence, fuzzy and interval uncertainties (Q1988196) (← links)
- Design optimization under uncertainties of a mesoscale implant in biological tissues using a probabilistic learning algorithm (Q1990872) (← links)
- Emulating dynamic non-linear simulators using Gaussian processes (Q2002727) (← links)
- Modelling of a thermomechanically coupled forming process based on functional outputs from a finite element analysis and from experimental measurements (Q2006885) (← links)
- Bayesian model calibration and optimization of surfactant-polymer flooding (Q2009830) (← links)
- Machine-learning in optimization of expensive black-box functions (Q2012143) (← links)
- Computation of the output of a function with fuzzy inputs based on a low-rank tensor approximation (Q2013835) (← links)
- Proper orthogonal decomposition, surrogate modelling and evolutionary optimization in aerodynamic design (Q2015955) (← links)
- Gradient-based methods for uncertainty quantification in hypersonic flows (Q2015969) (← links)
- Multi-fidelity deep neural network surrogate model for aerodynamic shape optimization (Q2020786) (← links)
- An efficient Kriging based method for time-dependent reliability based robust design optimization via evolutionary algorithm (Q2020995) (← links)
- A Bayesian approach for quantile optimization problems with high-dimensional uncertainty sources (Q2021998) (← links)
- Expected improvement for expensive optimization: a review (Q2022176) (← links)
- Stochastic optimization with adaptive restart: a framework for integrated local and global learning (Q2022223) (← links)
- Sequential model based optimization of partially defined functions under unknown constraints (Q2022235) (← links)
- Global optimization via inverse distance weighting and radial basis functions (Q2023666) (← links)
- An extended two-stage sequential optimization approach: properties and performance (Q2023982) (← links)
- Dataset2Vec: learning dataset meta-features (Q2036744) (← links)
- Black-box combinatorial optimization using models with integer-valued minima (Q2043440) (← links)
- Surrogate optimization of deep neural networks for groundwater predictions (Q2046338) (← links)
- Global optimization based on active preference learning with radial basis functions (Q2051251) (← links)
- MODES: model-based optimization on distributed embedded systems (Q2051343) (← links)
- Reliable crack detection in a rotor system with uncertainties via advanced simulation models based on kriging and polynomial chaos expansion (Q2063401) (← links)
- SMGO: a set membership approach to data-driven global optimization (Q2065241) (← links)
- Emulation-accelerated Hamiltonian Monte Carlo algorithms for parameter estimation and uncertainty quantification in differential equation models (Q2066738) (← links)
- Bayesian optimization of functional output in inverse problems (Q2069152) (← links)
- GOPS: efficient RBF surrogate global optimization algorithm with high dimensions and many parallel processors including application to multimodal water quality PDE model calibration (Q2069161) (← links)
- Data-driven spatial branch-and-bound algorithms for box-constrained simulation-based optimization (Q2070360) (← links)
- Fast selection of nonlinear mixed effect models using penalized likelihood (Q2072413) (← links)
- Biobjective robust simulation-based optimization for unconstrained problems (Q2077985) (← links)
- Uncertainty quantification of a computer model for binary black hole formation (Q2078270) (← links)
- A confidence-based aerospace design approach robust to structural turbulence closure uncertainty (Q2084092) (← links)
- Bayesian optimization approaches for identifying the best genotype from a candidate population (Q2084441) (← links)
- Sequential design strategy for kriging and cokriging-based machine learning in the context of reservoir history-matching (Q2085079) (← links)
- Batch sequential adaptive designs for global optimization (Q2089024) (← links)
- Reliability analysis of discrete-state performance functions via adaptive sequential sampling with detection of failure surfaces (Q2096838) (← links)
- \texttt{CAMERA}: a method for cost-aware, adaptive, multifidelity, efficient reliability analysis (Q2099759) (← links)
- Geometrically consistent aerodynamic optimization using an isogeometric discontinuous Galerkin method (Q2107212) (← links)
- Optimal budget allocation policy for tabu search in stochastic simulation optimization (Q2108143) (← links)
- Generalized hierarchical expected improvement method based on black-box functions of adaptive search strategy (Q2109428) (← links)
- Interval uncertainty propagation by a parallel Bayesian global optimization method (Q2109600) (← links)
- A Bayesian multiscale CNN framework to predict local stress fields in structures with microscale features (Q2115607) (← links)
- Bayesian optimization with output-weighted optimal sampling (Q2123965) (← links)
- Integrating \(\varepsilon \)-dominance and RBF surrogate optimization for solving computationally expensive many-objective optimization problems (Q2124811) (← links)
- Kriging-assisted teaching-learning-based optimization (KTLBO) to solve computationally expensive constrained problems (Q2127063) (← links)
- Symbolic DNN-tuner (Q2127252) (← links)
- Customized data-driven RANS closures for bi-fidelity LES-RANS optimization (Q2128496) (← links)
- Applying Bayesian optimization with Gaussian process regression to computational fluid dynamics problems (Q2136471) (← links)
- A novel surrogate-model based active learning method for structural reliability analysis (Q2136699) (← links)
