Approximative solutions to the bicriterion Vehicle Routing Problem with Time Windows. - Juliane Müller 002 (Eur. J. Oper. Res., 2010)

Surrogate Model Algorithms for Computationally Expensive Black-Box Global Optimization Problems. - Juliane Müller 002 (2012)

Programmable In Situ System for Iterative Workflows. - Erich Lohrmann; Zarija Lukic; Dmitriy Morozov; Juliane Müller 002 (JSSPP, 2017)

SOCEMO: Surrogate Optimization of Computationally Expensive Multiobjective Problems. - Juliane Müller 002 (INFORMS J. Comput., 2017)

GOSAC: global optimization with surrogate approximation of constraints. - Juliane Müller 002; Joshua D. Woodbury (J. Glob. Optim., 2017)

Adaptive Gaussian process surrogates for Bayesian inference. - Timur Takhtaganov; Juliane Müller 002 (CoRR, 2018)

Multivariate Rational Approximation. - Anthony P. Austin; Mohan Krishnamoorthy; Sven Leyffer; Stephen Mrenna; Juliane Müller 002; Holger Schulz (CoRR, 2019)

Surrogate Optimization of Computationally Expensive Black-Box Problems with Hidden Constraints. - Juliane Müller 002; Marcus Day (INFORMS J. Comput., 2019)

Classical Optimizers for Noisy Intermediate-Scale Quantum Devices. - Wim Lavrijsen; Ana Tudor; Juliane Müller 002; Costin Iancu; Wibe de Jong (QCE, 2020)

An algorithmic framework for the optimization of computationally expensive bi-fidelity black-box problems. - Juliane Müller 002 (INFOR Inf. Syst. Oper. Res., 2020)

HYPPO: A Surrogate-Based Multi-Level Parallelism Tool for Hyperparameter Optimization. - Vincent Dumont; Casey Garner; Anuradha Trivedi; Chelsea Jones; Vidya Ganapati; Juliane Mueller 002; Talita Perciano; Mariam Kiran; Marc Day (MLHPC@SC, 2021)

Assessing data change in scientific datasets. - Juliane Müller 002; Boris Faybishenko; Deborah A. Agarwal; Stephen Bailey; Chongya Jiang; Youngryel Ryu; Craig Tull; Lavanya Ramakrishnan (Concurr. Comput. Pract. Exp., 2021)

BROOD: Bilevel and Robust Optimization and Outlier Detection for Efficient Tuning of High-Energy Physics Event Generators. - Wenjing Wang; Mohan Krishnamoorthy; Juliane Müller 002; Stephen Mrenna; Holger Schulz; Xiangyang Ju; Sven Leyffer; Zachary Marshall (CoRR, 2021)

Learning from learning machines: a new generation of AI technology to meet the needs of science. - Luca Pion-Tonachini; Kristofer E. Bouchard; Héctor García Martín; Sean Peisert; W. Bradley Holtz; Anil Aswani; Dipankar Dwivedi; Haruko M. Wainwright; Ghanshyam Pilania; Benjamin Nachman; Babetta L. Marrone; Nicola Falco; et al. (CoRR, 2021)

Practical algorithms for multivariate rational approximation. - Anthony P. Austin; Mohan Krishnamoorthy; Sven Leyffer; Stephen Mrenna; Juliane Müller 002; Holger Schulz (Comput. Phys. Commun., 2021)

Surrogate optimization of deep neural networks for groundwater predictions. - Juliane Müller 002; Jangho Park; Reetik Sahu; Charuleka Varadharajan; Bhavna Arora; Boris Faybishenko; Deborah A. Agarwal (J. Glob. Optim., 2021)

Accelerating Noisy VQE Optimization with Gaussian Processes. - Juliane Müller 002; Wim Lavrijsen; Costin Iancu; Wibe de Jong (QCE, 2022)

Hyperparameter Optimization of Generative Adversarial Network Models for High-Energy Physics Simulations. - Vincent Dumont; Xiangyang Ju; Juliane Mueller 002 (CoRR, 2022)

A Self-Supervised Approach to Reconstruction in Sparse X-Ray Computed Tomography. - Rey Mendoza; Minh Nguyen; Judith Weng Zhu; Vincent Dumont; Talita Perciano; Juliane Mueller 002; Vidya Ganapati (CoRR, 2022)

Efficient Inverse Design Optimization through Multi-fidelity Simulations, Machine Learning, and Search Space Reduction Strategies. - Luka Grbcic; Juliane Müller 002; Wibe Albert de Jong (CoRR, 2023)

Long-term missing value imputation for time series data using deep neural networks. - Jangho Park; Juliane Müller 002; Bhavna Arora; Boris Faybishenko; Gilberto Zonta Pastorello; Charuleka Varadharajan; Reetik Sahu; Deborah A. Agarwal (Neural Comput. Appl., 2023)

Welcome Message from LLMxHPC Workshop. - Kevin A. Brown; Tanwi Mallick; Juliane Mueller 002; Aleksandr Drozd (CLUSTER Workshops, 2024)

Inverse design of photonic surfaces on Inconel via multi-fidelity machine learning ensemble framework and high throughput femtosecond laser processing. - Luka Grbcic; Minok Park; Mahmoud Elzouka; Ravi Prasher; Juliane Müller 002; Costas P. Grigoropoulos; Sean D. Lubner; Vassilia Zorba; Wibe Albert de Jong (CoRR, 2024)

AI Driven Laser Parameter Search: Inverse Design of Photonic Surfaces using Greedy Surrogate-based Optimization. - Luka Grbcic; Minok Park; Juliane Müller 002; Vassilia Zorba; Wibe Albert de Jong (CoRR, 2024)

Dispersion-enhanced sequential batch sampling for adaptive contour estimation. - Yiming Che; Juliane Müller 002; Changqing Cheng (Qual. Reliab. Eng. Int., 2024)

Efficient inverse design optimization through multi-fidelity simulations, machine learning, and boundary refinement strategies. - Luka Grbcic; Juliane Müller 002; Wibe Albert de Jong (Eng. Comput., 2024)

Adaptive Computing for Scale-Up Problems. - Kevin Patrick Griffin; Hilary Egan; Marc T. Henry de Frahan; Juliane Mueller 002; Deepthi Vaidhynathan; Dylan Wald; Rohit Chintala; Olga A. Doronina; Hariswaran Sitaraman; Ethan Young; Ryan King; Jibonananda Sanyal; et al. (Comput. Sci. Eng., 2025)

Artificial intelligence driven laser parameter search: Inverse design of photonic surfaces using greedy surrogate-based optimization. - Luka Grbcic; Minok Park; Juliane Mueller 002; Vassilia Zorba; Wibe Albert de Jong (Eng. Appl. Artif. Intell., 2025)

Convergence of Energy and IT Sectors. - Cullen E. Bash; John McDonald 006; Dejan S. Milojicic; Juliane Mueller 002; Tom Wilson; Ying Zhang 022 (Computer, 2025)

AutoTandemML: Active Learning Enhanced Tandem Neural Networks for Inverse Design Problems. - Luka Grbcic; Juliane Mueller 002; Wibe Albert de Jong (CoRR, 2025)