Juliane Mueller

According to our database, Juliane Mueller authored at least 31 papers between 2010 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Multi-modal Bayesian Neural Network Surrogates with Conjugate Last-Layer Estimation.

Ian Taylor, Juliane Mueller, Julie Bessac

CoRR, September, 2025

Convergence of Energy and IT Sectors.

Cullen E. Bash, John McDonald, Dejan S. Milojicic, Juliane Mueller, Tom Wilson, Ying Zhang

Computer, January, 2025

Artificial intelligence driven laser parameter search: Inverse design of photonic surfaces using greedy surrogate-based optimization.

Luka Grbcic, Minok Park, Juliane Mueller, Vassilia Zorba, Wibe Albert de Jong

Eng. Appl. Artif. Intell., 2025

Adaptive Computing for Scale-Up Problems.

Kevin Patrick Griffin, Hilary Egan, Marc T. Henry de Frahan, Juliane Mueller, Deepthi Vaidhynathan, Dylan Wald, Rohit Chintala, Olga A. Doronina, Hariswaran Sitaraman, Ethan Young, Ryan King, Jibonananda Sanyal, Marc Day, Ross E. Larsen

Comput. Sci. Eng., 2025

AutoTandemML: Active learning enhanced tandem neural networks for inverse design problems.

Luka Grbcic, Juliane Müller, Wibe Albert de Jong

Appl. Soft Comput., 2025

2024

Efficient inverse design optimization through multi-fidelity simulations, machine learning, and boundary refinement strategies.

Luka Grbcic, Juliane Müller, Wibe Albert de Jong

Eng. Comput., December, 2024

Dispersion-enhanced sequential batch sampling for adaptive contour estimation.

Yiming Che, Juliane Müller, Changqing Cheng

Qual. Reliab. Eng. Int., February, 2024

AI Driven Laser Parameter Search: Inverse Design of Photonic Surfaces using Greedy Surrogate-based Optimization.

Luka Grbcic, Minok Park, Juliane Müller, Vassilia Zorba, Wibe Albert de Jong

CoRR, 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, Costas P. Grigoropoulos, Sean D. Lubner, Vassilia Zorba, Wibe Albert de Jong

CoRR, 2024

Welcome Message from LLMxHPC Workshop.

Kevin A. Brown, Tanwi Mallick, Juliane Mueller, Aleksandr Drozd

Proceedings of the IEEE International Conference on Cluster Computing, 2024

2023

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

Jangho Park, Juliane Müller, Bhavna Arora, Boris Faybishenko, Gilberto Zonta Pastorello, Charuleka Varadharajan, Reetik Sahu, Deborah A. Agarwal

Neural Comput. Appl., April, 2023

Efficient Inverse Design Optimization through Multi-fidelity Simulations, Machine Learning, and Search Space Reduction Strategies.

Luka Grbcic, Juliane Müller, Wibe Albert de Jong

CoRR, 2023

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, Vidya Ganapati

CoRR, 2022

Hyperparameter Optimization of Generative Adversarial Network Models for High-Energy Physics Simulations.

Vincent Dumont, Xiangyang Ju, Juliane Mueller

CoRR, 2022

Accelerating Noisy VQE Optimization with Gaussian Processes.

Juliane Müller, Wim Lavrijsen, Costin Iancu, Wibe de Jong

Proceedings of the IEEE International Conference on Quantum Computing and Engineering, 2022

2021

Surrogate optimization of deep neural networks for groundwater predictions.

Juliane Müller, Jangho Park, Reetik Sahu, Charuleka Varadharajan, Bhavna Arora, Boris Faybishenko, Deborah A. Agarwal

J. Glob. Optim., 2021

Practical algorithms for multivariate rational approximation.

Anthony P. Austin, Mohan Krishnamoorthy, Sven Leyffer, Stephen Mrenna, Juliane Müller, Holger Schulz

Comput. Phys. Commun., 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, Prabhat, Daniel B. Arnold, Alejandro Wolf-Yadlin, Sarah Powers, Sharlee Climer, Quinn Jackson, Ty Carlson, Michael Sohn, Petrus H. Zwart, Neeraj Kumar, Amy Justice, Claire J. Tomlin, Daniel A. Jacobson, Gos Micklem, Georgios V. Gkoutos, Peter J. Bickel, Jean-Baptiste Cazier, Juliane Müller, Bobbie-Jo Webb-Robertson, Rick Stevens, Mark Anderson, Kenneth Kreutz-Delgado, Michael W. Mahoney, James B. Brown

CoRR, 2021

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

Wenjing Wang, Mohan Krishnamoorthy, Juliane Müller, Stephen Mrenna, Holger Schulz, Xiangyang Ju, Sven Leyffer, Zachary Marshall

CoRR, 2021

Assessing data change in scientific datasets.

Juliane Müller, Boris Faybishenko, Deborah A. Agarwal, Stephen Bailey, Chongya Jiang, Youngryel Ryu, Craig Tull, Lavanya Ramakrishnan

Concurr. Comput. Pract. Exp., 2021

HYPPO: A Surrogate-Based Multi-Level Parallelism Tool for Hyperparameter Optimization.

Vincent Dumont, Casey Garner, Anuradha Trivedi, Chelsea Jones, Vidya Ganapati, Juliane Mueller, Talita Perciano, Mariam Kiran, Marc Day

Proceedings of the IEEE/ACM Workshop on Machine Learning in High Performance Computing Environments, 2021

2020

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

Juliane Müller

INFOR Inf. Syst. Oper. Res., 2020

Classical Optimizers for Noisy Intermediate-Scale Quantum Devices.

Wim Lavrijsen, Ana Tudor, Juliane Müller, Costin Iancu, Wibe de Jong

Proceedings of the IEEE International Conference on Quantum Computing and Engineering, 2020

2019

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

Juliane Müller, Marcus Day

INFORMS J. Comput., 2019

Multivariate Rational Approximation.

Anthony P. Austin, Mohan Krishnamoorthy, Sven Leyffer, Stephen Mrenna, Juliane Müller, Holger Schulz

CoRR, 2019

2018

Adaptive Gaussian process surrogates for Bayesian inference.

Timur Takhtaganov, Juliane Müller

CoRR, 2018

2017

GOSAC: global optimization with surrogate approximation of constraints.

Juliane Müller, Joshua D. Woodbury

J. Glob. Optim., 2017

SOCEMO: Surrogate Optimization of Computationally Expensive Multiobjective Problems.

Juliane Müller

INFORMS J. Comput., 2017

Programmable In Situ System for Iterative Workflows.

Erich Lohrmann, Zarija Lukic, Dmitriy Morozov, Juliane Müller

Proceedings of the Job Scheduling Strategies for Parallel Processing, 2017

2012

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

Juliane Müller

PhD thesis, 2012

2010

Approximative solutions to the bicriterion Vehicle Routing Problem with Time Windows.

Juliane Müller

Eur. J. Oper. Res., 2010