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Marcus Michael Noack

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affiliation: Lawrence Berkeley National Laboratory, Berkeley, CA, USA

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Journal Articles

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2020
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  - journals/mlst/MeltonNOBRZBJKZ20
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Charles N. Melton, Marcus Michael Noack, Taisuke Ohta, Thomas E. Beechem, Jeremy Robinson, Xiaotian Zhang, Aaron Bostwick, Chris Jozwiak, Roland J. Koch, Petrus H. Zwart, Alexander Hexemer, Eli Rotenberg:
K-means-driven Gaussian Process data collection for angle-resolved photoemission spectroscopy. Mach. Learn. Sci. Technol. 1(4): 45015 (2020)
2017
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Marcus Michael Noack, Simon W. Funke:
Hybrid genetic deflated Newton method for global optimisation. J. Comput. Appl. Math. 325: 97-112 (2017)
2015
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Marcus Michael Noack:
A two-scale method using a list of active sub-domains for a fully parallelized solution of wave equations. J. Comput. Sci. 11: 91-101 (2015)

Conference and Workshop Papers

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2021
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  - conf/xloop-ws/NoackPKZ21
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Marcus Michael Noack, David Perryman, Harinarayan Krishnan, Petrus H. Zwart:
High-Performance Hybrid-Global-Deflated-Local Optimization with Applications to Active Learning. XLOOP@SC 2021: 24-29
2019
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Marcus Michael Noack, Petrus H. Zwart:
Computational Strategies to Increase Efficiency of Gaussian-Process-Driven Autonomous Experiments. XLOOP@SC 2019: 1-7
2014
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  - conf/miccai/McLeodNSH14
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Kristin McLeod, Marcus Michael Noack, Jørg Saberniak, Kristina Haugaa:
Structural Abnormality Detection of ARVC Patients via Localised Distance-to-Average Mapping. STACOM 2014: 177-186

Informal and Other Publications

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2023
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  - journals/corr/abs-2309-10068
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Marcus Michael Noack, Hengrui Luo, Mark D. Risser:
A Unifying Perspective on Non-Stationary Kernels for Deeper Gaussian Processes. CoRR abs/2309.10068 (2023)
2022
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  - journals/corr/abs-2205-09070
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Marcus Michael Noack, Harinarayan Krishnan, Mark D. Risser, Kristofer G. Reyes:
Exact Gaussian Processes for Massive Datasets via Non-Stationary Sparsity-Discovering Kernels. CoRR abs/2205.09070 (2022)
2021
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  - journals/corr/abs-2102-03432
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Marcus Michael Noack, James A. Sethian:
Advanced Stationary and Non-Stationary Kernel Designs for Domain-Aware Gaussian Processes. CoRR abs/2102.03432 (2021)

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