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Ben Moseley

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affiliation: ETH Zürich, AI Center, Switzerland
affiliation (PhD 2022): University of Oxford, UK

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2020 – today

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2024
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  - journals/ram/DelgadoCentenoHBMKGO24
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Jose Ignacio Delgado-Centeno, Paula Harder, Valentin Tertius Bickel, Ben Moseley, Freddie Kalaitzis, Siddha Ganju, Miguel A. Olivares-Méndez:
Superresolution of Lunar Satellite Images for Enhanced Robotic Traverse Planning: Maximizing the Value of Existing Data Products for Space Robotics. IEEE Robotics Autom. Mag. 31(2): 100-112 (2024)
2023
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Ben Moseley, Andrew Markham, Tarje Nissen-Meyer:
Finite basis physics-informed neural networks (FBPINNs): a scalable domain decomposition approach for solving differential equations. Adv. Comput. Math. 49(4): 62 (2023)
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  - journals/corr/abs-2306-05486
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Victorita Dolean, Alexander Heinlein, Siddhartha Mishra, Ben Moseley:
Multilevel domain decomposition-based architectures for physics-informed neural networks. CoRR abs/2306.05486 (2023)
2022
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Ben Moseley:
Physics-informed machine learning: from concepts to real-world applications. University of Oxford, UK, 2022
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  - journals/corr/abs-2211-05560
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Victorita Dolean, Alexander Heinlein, Siddhartha Mishra, Ben Moseley:
Finite basis physics-informed neural networks as a Schwarz domain decomposition method. CoRR abs/2211.05560 (2022)
2021
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  - conf/cvpr/MoseleyBFR21
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Ben Moseley, Valentin Tertius Bickel, Ignacio G. Lopez Francos, Loveneesh Rana:
Extreme Low-Light Environment-Driven Image Denoising Over Permanently Shadowed Lunar Regions With a Physical Noise Model. CVPR 2021: 6317-6327
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  - journals/corr/abs-2107-07871
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Ben Moseley, Andrew Markham, Tarje Nissen-Meyer:
Finite Basis Physics-Informed Neural Networks (FBPINNs): a scalable domain decomposition approach for solving differential equations. CoRR abs/2107.07871 (2021)

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