Michael Grosskopf
Orcid: 0000-0002-7838-3609
According to our database1,
Michael Grosskopf
authored at least 19 papers
between 2011 and 2025.
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Bibliography
2025
A Partitioned Sparse Variational Gaussian Process for Fast, Distributed Spatial Modeling.
CoRR, July, 2025
Identifying Nuclear Data Correlated Through Predicting Bias in Integral Experiments via Applying Principal Component Analysis to Random Forest.
Stat. Anal. Data Min., 2025
Machine learning-assisted identification of potential sources of bias in measurements of prompt-fission neutron spectra.
Comput. Phys. Commun., 2025
2024
Bayesian batch optimization for molybdenum versus tungsten inertial confinement fusion double shell target design.
Stat. Anal. Data Min., June, 2024
Stat. Anal. Data Min., April, 2024
Stat. Anal. Data Min., February, 2024
2022
Technometrics, 2022
Fast emulation of density functional theory simulations using approximate Gaussian processes.
CoRR, 2022
2021
Technometrics, 2021
Proceedings of the ISAV@SC 21: In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization, 2021
Fast Gaussian Process Estimation for Large-Scale In Situ Inference using Convolutional Neural Networks.
Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021
2020
Identifying Entangled Physics Relationships through Sparse Matrix Decomposition to Inform Plasma Fusion Design.
CoRR, 2020
Exploring Sensitivity of ICF Outputs to Design Parameters in Experiments Using Machine Learning.
CoRR, 2020
Proceedings of the 50th Annual IEEE/IFIP International Conference on Dependable Systems and Networks, 2020
2017
Technometrics, 2017
2013
Prediction and Computer Model Calibration Using Outputs From Multifidelity Simulators.
Technometrics, 2013
2011
Reliab. Eng. Syst. Saf., 2011