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Nick Luiken
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2020 – today
- 2024
- [j5]Matteo Ravasi, Marcus Valtonen Örnhag, Nick Luiken, Olivier Leblanc, Eneko Uruñuela:
PyProximal - scalable convex optimization in Python. J. Open Source Softw. 9(96): 6326 (2024) - 2023
- [c1]Nick Luiken, Matteo Ravasi:
A deep learning-based approach to increase efficiency in the acquisition of ultrasonic non-destructive testing datasets. CVPR Workshops 2023: 3094-3102 - [i4]Juan Romero, Wolfgang Heidrich, Nick Luiken, Matteo Ravasi:
IntraSeismic: a coordinate-based learning approach to seismic inversion. CoRR abs/2312.10568 (2023) - 2022
- [j4]Matteo Ravasi, Tamin Selvan, Nick Luiken:
Stochastic Multi-Dimensional Deconvolution. IEEE Trans. Geosci. Remote. Sens. 60: 1-14 (2022) - [i3]Nick Luiken, Matteo Ravasi, Claire E. Birnie:
A hybrid approach to seismic deblending: when physics meets self-supervision. CoRR abs/2205.15395 (2022) - [i2]Muhammad Izzatullah, Tariq Alkhalifah, Juan Romero, Miguel Corrales, Nick Luiken, Matteo Ravasi:
Posterior sampling with CNN-based, Plug-and-Play regularization with applications to Post-Stack Seismic Inversion. CoRR abs/2212.14595 (2022) - 2021
- [j3]David Vargas, Ivan Vasconcelos, Matteo Ravasi, Nick Luiken:
Time-Domain Multidimensional Deconvolution: A Physically Reliable and Stable Preconditioned Implementation. Remote. Sens. 13(18): 3683 (2021) - [j2]Nick Luiken, Tristan van Leeuwen:
Relaxed Regularization for Linear Inverse Problems. SIAM J. Sci. Comput. 43(5): S269-S292 (2021) - 2020
- [j1]Nick Luiken, Tristan van Leeuwen:
Comparing RSVD and Krylov methods for linear inverse problems. Comput. Geosci. 137: 104427 (2020) - [i1]Nick Luiken, Tristan van Leeuwen:
Relaxed regularization for linear inverse problems. CoRR abs/2006.14987 (2020)
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