Juliane Müller

发表

MISO: mixed-integer surrogate optimization framework

Juliane Müller, 2016 .

CH 4 parameter estimation in CLM4.5bgc using surrogate global optimization

Christine A. Shoemaker, Yilun Wang, Rajendra Paudel, 2015 .

Surrogate optimization of deep neural networks for groundwater predictions

D. Agarwal, Juliane Müller, B. Faybishenko, 2019, Journal of Global Optimization.

Multivariate Rational Approximation pdf

Sven Leyffer, Anthony P. Austin, Juliane Muller, 2019, ArXiv.

SO-I: a surrogate model algorithm for expensive nonlinear integer programming problems including global optimization applications

C. Shoemaker, R. Piché, Juliane Müller, 2013, Journal of Global Optimization.

GOSAC: global optimization with surrogate approximation of constraints

Juliane Müller, J. Woodbury, 2017, Journal of Global Optimization.

MISO: mixed-integer surrogate optimization framework

Juliane Müller, 2015, Optimization and Engineering.

Surrogate optimization of deep neural networks for groundwater predictions

Juliane Müller, B. Faybishenko, C. Varadharajan, 2020, Journal of Global Optimization.

Adaptive Gaussian process surrogates for Bayesian inference pdf

Juliane Müller, Timur Takhtaganov, Juliane Müller, 2018, ArXiv.

An Efficient Algorithm for Automatic Structure Optimization in X-ray Standing-Wave Experiments

James A. Sethian, Osman Karsliouglu, Mathias Gehlmann, 2018, Journal of Electron Spectroscopy and Related Phenomena.

Assessing data change in scientific datasets

Lavanya Ramakrishnan, Deborah A. Agarwal, Youngryel Ryu, 2021, Concurr. Comput. Pract. Exp..

SO-I: a surrogate model algorithm for expensive nonlinear integer programming problems including global optimization applications

Christine A. Shoemaker, Robert Piché, Juliane Müller, 2014, J. Glob. Optim..

MATSuMoTo: The MATLAB Surrogate Model Toolbox For Computationally Expensive Black-Box Global Optimization Problems

Juliane Müller, Juliane Müller, 2014, 1404.4261.

Surrogate Model Algorithms for Computationally Expensive Black-Box Global Optimization Problems

Juliane Müller, Juliane Müller, 2012 .

Influence of ensemble surrogate models and sampling strategy on the solution quality of algorithms for computationally expensive black-box global optimization problems

Juliane Müller, Juliane Müller, Christine A. Shoemaker, 2014, Journal of Global Optimization.

Influence of ensemble surrogate models and sampling strategy on the solution quality of algorithms for computationally expensive black-box global optimization problems

Christine A. Shoemaker, Juliane Müller, C. Shoemaker, 2014, J. Glob. Optim..

SO-MODS: Optimization for high dimensional computationally expensive multi-modal functions with surrogate search

Christine A. Shoemaker, Tipaluck Krityakierne, Juliane Müller, 2014, 2014 IEEE Congress on Evolutionary Computation (CEC).

An algorithmic framework for the optimization of computationally expensive bi-fidelity black-box problems

Juliane Müller, Juliane Müller, 2020, INFOR Inf. Syst. Oper. Res..

GOSAC: global optimization with surrogate approximation of constraints

Juliane Müller, Joshua D. Woodbury, Juliane Müller, 2017, J. Glob. Optim..

SO-MI: A surrogate model algorithm for computationally expensive nonlinear mixed-integer black-box global optimization problems

Christine A. Shoemaker, Robert Piché, Juliane Müller, 2013, Comput. Oper. Res..

Impact of Input Feature Selection on Groundwater Level Prediction From a Multi-Layer Perceptron Neural Network

Jangho Park, Reetik Kumar Sahu, Bhavna Arora, 2020, Frontiers in Water.

Classical Optimizers for Noisy Intermediate-Scale Quantum Devices

Costin Iancu, Wim Lavrijsen, Ana Tudor, 2020, 2020 IEEE International Conference on Quantum Computing and Engineering (QCE).

BROOD: Bilevel and Robust Optimization and Outlier Detection for Efficient Tuning of High-Energy Physics Event Generators pdf

Sven Leyffer, Stephen Mrenna, Xiangyang Ju, 2021, SciPost Physics Core.

SOCEMO: Surrogate Optimization of Computationally Expensive Multiobjective Problems

Juliane Müller, Juliane Müller, 2017, INFORMS J. Comput..

Practical algorithms for multivariate rational approximation

Sven Leyffer, Anthony P. Austin, Stephen Mrenna, 2020, Comput. Phys. Commun..

Mixture surrogate models based on Dempster-Shafer theory for global optimization problems

Robert Piché, Juliane Müller, R. Piché, 2011, J. Glob. Optim..

Surrogate Optimization of Computationally Expensive Black-Box Problems with Hidden Constraints

Juliane Müller, Marcus Day, Juliane Müller, 2019, INFORMS J. Comput..

Cosmic Inference: Constraining Parameters with Observations and a Highly Limited Number of Simulations

Dmitriy Morozov, Zarija Lukic, Timur Takhtaganov, 2019, The Astrophysical Journal.

Long-term missing value imputation for time series data using deep neural networks

Juliane Müller, B. Faybishenko, G. Pastorello, 2022, Neural Computing and Applications.

Calibration of GARCH models using concurrent accelerated random search

Robert Piché, Juho Kanniainen, Juliane Müller, 2013, Appl. Math. Comput..

Long-term missing value imputation for time series data using deep neural networks

Juliane Müller, B. Faybishenko, G. Pastorello, 2022, Neural Computing and Applications.