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ORCIDBen Moseley
Person information
- affiliation: ETH Zürich, AI Center, Switzerland
- affiliation (PhD 2022): University of Oxford, UK
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2020 – today
- 2024
[j2]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)- [i4]Samuel Anderson, Victorita Dolean, Ben Moseley, Jennifer Pestana:
ELM-FBPINN: efficient finite-basis physics-informed neural networks. CoRR abs/2409.01949 (2024) - 2023
- [j1]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) - [i3]Victorita Dolean, Alexander Heinlein, Siddhartha Mishra, Ben Moseley:
Multilevel domain decomposition-based architectures for physics-informed neural networks. CoRR abs/2306.05486 (2023) - 2022
- [b1]Ben Moseley:
Physics-informed machine learning: from concepts to real-world applications. University of Oxford, UK, 2022 - [i2]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
- [c1]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 - [i1]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)
Coauthor Index
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