Juliane Müller

25 papers C 1Misc 2Journal 21

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	AutoTandemML: Active learning enhanced tandem neural networks for inverse design problems. Appl. Soft Comput. Luka Grbcic, Juliane Müller, Wibe Albert de Jong
2024	J	`jnl`	AI Driven Laser Parameter Search: Inverse Design of Photonic Surfaces using Greedy Surrogate-based Optimization. CoRR Luka Grbcic, Minok Park, Juliane Müller, Vassilia Zorba, Wibe Albert de Jong
2024	J	`jnl`	Dispersion-enhanced sequential batch sampling for adaptive contour estimation. Qual. Reliab. Eng. Int. Yiming Che, Juliane Müller, Changqing Cheng
2024	J	`jnl`	Efficient inverse design optimization through multi-fidelity simulations, machine learning, and boundary refinement strategies. Eng. Comput. Luka Grbcic, Juliane Müller, Wibe Albert de Jong
2024	J	`jnl`	Inverse design of photonic surfaces on Inconel via multi-fidelity machine learning ensemble framework and high throughput femtosecond laser processing. CoRR Luka Grbcic, Minok Park, Mahmoud Elzouka, Ravi Prasher, Juliane Müller, Costas P. Grigoropoulos, Sean D. Lubner, Vassilia Zorba, Wibe Albert de Jong
2023	J	`jnl`	Efficient Inverse Design Optimization through Multi-fidelity Simulations, Machine Learning, and Search Space Reduction Strategies. CoRR Luka Grbcic, Juliane Müller, Wibe Albert de Jong
2023	J	`jnl`	Long-term missing value imputation for time series data using deep neural networks. Neural Comput. Appl. Jangho Park, Juliane Müller, Bhavna Arora, Boris Faybishenko, Gilberto Zonta Pastorello, Charuleka Varadharajan, Reetik Sahu, Deborah A. Agarwal
2022	Misc	`conf`	Accelerating Noisy VQE Optimization with Gaussian Processes. QCE Juliane Müller, Wim Lavrijsen, Costin Iancu, Wibe de Jong
2022	J	`jnl`	Long-Term Missing Value Imputation for Time Series Data Using Deep Neural Networks. CoRR Jangho Park, Juliane Müller, Bhavna Arora, Boris Faybishenko, Gilberto Zonta Pastorello, Charuleka Varadharajan, Reetik Sahu, Deborah A. Agarwal
2021	J	`jnl`	Assessing data change in scientific datasets. Concurr. Comput. Pract. Exp. Juliane Müller, Boris Faybishenko, Deborah A. Agarwal, Stephen Bailey, Chongya Jiang, Youngryel Ryu, Craig Tull, Lavanya Ramakrishnan
2021	J	`jnl`	BROOD: Bilevel and Robust Optimization and Outlier Detection for Efficient Tuning of High-Energy Physics Event Generators. CoRR Wenjing Wang, Mohan Krishnamoorthy, Juliane Müller, Stephen Mrenna, Holger Schulz, Xiangyang Ju, Sven Leyffer, Zachary Marshall
2021	J	`jnl`	Learning from learning machines: a new generation of AI technology to meet the needs of science. CoRR 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
2021	J	`jnl`	Practical algorithms for multivariate rational approximation. Comput. Phys. Commun. Anthony P. Austin, Mohan Krishnamoorthy, Sven Leyffer, Stephen Mrenna, Juliane Müller, Holger Schulz
2021	J	`jnl`	Surrogate optimization of deep neural networks for groundwater predictions. J. Glob. Optim. Juliane Müller, Jangho Park, Reetik Sahu, Charuleka Varadharajan, Bhavna Arora, Boris Faybishenko, Deborah A. Agarwal
2020	J	`jnl`	An algorithmic framework for the optimization of computationally expensive bi-fidelity black-box problems. INFOR Inf. Syst. Oper. Res. Juliane Müller
2020	Misc	`conf`	Classical Optimizers for Noisy Intermediate-Scale Quantum Devices. QCE Wim Lavrijsen, Ana Tudor, Juliane Müller, Costin Iancu, Wibe de Jong
2019	J	`jnl`	Multivariate Rational Approximation. CoRR Anthony P. Austin, Mohan Krishnamoorthy, Sven Leyffer, Stephen Mrenna, Juliane Müller, Holger Schulz
2019	J	`jnl`	Surrogate Optimization of Computationally Expensive Black-Box Problems with Hidden Constraints. INFORMS J. Comput. Juliane Müller, Marcus Day
2019	J	`jnl`	Surrogate Optimization of Deep Neural Networks for Groundwater Predictions. CoRR Juliane Müller, Jangho Park, Reetik Sahu, Charuleka Varadharajan, Bhavna Arora, Boris Faybishenko, Deborah A. Agarwal
2018	J	`jnl`	Adaptive Gaussian process surrogates for Bayesian inference. CoRR Timur Takhtaganov, Juliane Müller
2017	J	`jnl`	GOSAC: global optimization with surrogate approximation of constraints. J. Glob. Optim. Juliane Müller, Joshua D. Woodbury
2017	C	`conf`	Programmable In Situ System for Iterative Workflows. JSSPP Erich Lohrmann, Zarija Lukic, Dmitriy Morozov, Juliane Müller
2017	J	`jnl`	SOCEMO: Surrogate Optimization of Computationally Expensive Multiobjective Problems. INFORMS J. Comput. Juliane Müller
2012	—	`—`	Surrogate Model Algorithms for Computationally Expensive Black-Box Global Optimization Problems. Juliane Müller
2010	J	`jnl`	Approximative solutions to the bicriterion Vehicle Routing Problem with Time Windows. Eur. J. Oper. Res. Juliane Müller