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2020 – today
- 2024
[j8]Yuxi Hong
, Hatem Ltaief, Matteo Ravasi, David E. Keyes:
High performance computing seismic redatuming by inversion with algebraic compression and multiple precisions. Int. J. High Perform. Comput. Appl. 38(3): 225-244 (2024)- [j7]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) - [i10]Daria Sushnikova, Matteo Ravasi, David E. Keyes:
Multidimensional deconvolution with shared bases. CoRR abs/2404.01870 (2024) - 2023
- [c3]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 - [c2]Hatem Ltaief, Yuxi Hong, Leighton Wilson, Mathias Jacquelin, Matteo Ravasi, David Elliot Keyes:
Scaling the "Memory Wall" for Multi-Dimensional Seismic Processing with Algebraic Compression on Cerebras CS-2 Systems. SC 2023: 6:1-6:12 - [c1]Hatem Ltaief, Yuxi Hong, Adel Dabah, Rabab Alomairy, Sameh Abdulah, Chris Goreczny, Pawel Gepner, Matteo Ravasi, Damien Gratadour, David E. Keyes:
Steering Customized AI Architectures for HPC Scientific Applications. ISC 2023: 125-143 - [i9]Francesco Brandolin, Matteo Ravasi, Tariq Alkhalifah:
PINNslope: seismic data interpolation and local slope estimation with physics informed neural networks. CoRR abs/2305.15990 (2023) - [i8]Claire Birnie, Matteo Ravasi:
Explainable Artificial Intelligence driven mask design for self-supervised seismic denoising. CoRR abs/2307.06682 (2023) - [i7]Juan Romero, Wolfgang Heidrich, Nick Luiken, Matteo Ravasi:
IntraSeismic: a coordinate-based learning approach to seismic inversion. CoRR abs/2312.10568 (2023) - 2022
- [j6]Hatem Ltaief, Marc G. Genton, Damien Gratadour, David E. Keyes, Matteo Ravasi:
Responsibly Reckless Matrix Algorithms for HPC Scientific Applications. Comput. Sci. Eng. 24(4): 12-22 (2022) - [j5]Weiwei Xu, Vincenzo Lipari, Paolo Bestagini, Matteo Ravasi, Wenchao Chen, Stefano Tubaro:
Intelligent Seismic Deblending Through Deep Preconditioner. IEEE Geosci. Remote. Sens. Lett. 19: 1-5 (2022) - [j4]Matteo Ravasi, Tamin Selvan, Nick Luiken:
Stochastic Multi-Dimensional Deconvolution. IEEE Trans. Geosci. Remote. Sens. 60: 1-14 (2022) - [i6]Nick Luiken, Matteo Ravasi, Claire E. Birnie:
A hybrid approach to seismic deblending: when physics meets self-supervision. CoRR abs/2205.15395 (2022) - [i5]Matteo Ravasi:
Deep Preconditioners and their application to seismic wavefield processing. CoRR abs/2207.09938 (2022) - [i4]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]Yuxi Hong, Hatem Ltaief, Matteo Ravasi, Laurent Gatineau, David E. Keyes:
Accelerating Seismic Redatuming Using Tile Low-Rank Approximations on NEC SX-Aurora TSUBASA. Supercomput. Front. Innov. 8(2): 6-26 (2021) - [i3]Claire Birnie, Matteo Ravasi, Tariq Alkhalifah, Sixiu Liu:
The potential of self-supervised networks for random noise suppression in seismic data. CoRR abs/2109.07344 (2021) - 2020
- [j1]Matteo Ravasi, Ivan Vasconcelos:
PyLops - A linear-operator Python library for scalable algebra and optimization. SoftwareX 11: 100361 (2020) - [i2]Matteo Ravasi, Ivan Vasconcelos:
On the implementation of large-scale integral operators with modern HPC solutions - Application to 3D Marchenko imaging by least-squares inversion. CoRR abs/2011.11120 (2020)
2010 – 2019
- 2019
- [i1]Matteo Ravasi, Ivan Vasconcelos:
PyLops - A Linear-Operator Python Library for large scale optimization. CoRR abs/1907.12349 (2019)
Coauthor Index
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