Matteo Ravasi

25 papers A 1C 1Journal 22Unranked 1
YearRankTypeTitle / Venue / Authors
2025 J jnl
Geophysical inverse problems with measurement-guided diffusion models.
CoRR
Matteo Ravasi
2025 J jnl
Leveraging Low-Rank and ℋ
J. Sci. Comput.
Daria Sushnikova, Matteo Ravasi, David E. Keyes
2025 J jnl
PyLops-MPI - MPI Powered PyLops with mpi4py.
J. Open Source Softw.
Rohan Babbar, Matteo Ravasi, Yuxi Hong
2025 J jnl
Uncertainty Quantification in HSI Reconstruction using Physics-Aware Diffusion Priors and Optics-Encoded Measurements.
CoRR
Juan Romero, Qiang Fu, Matteo Ravasi, Wolfgang Heidrich
2024 J jnl
High performance computing seismic redatuming by inversion with algebraic compression and multiple precisions.
Int. J. High Perform. Comput. Appl.
Yuxi Hong, Hatem Ltaief, Matteo Ravasi, David E. Keyes
2024 J jnl
Multidimensional deconvolution with shared bases.
CoRR
Daria Sushnikova, Matteo Ravasi, David E. Keyes
2024 J jnl
PyProximal - scalable convex optimization in Python.
J. Open Source Softw.
Matteo Ravasi, Marcus Valtonen Örnhag, Nick Luiken, Olivier Leblanc, Eneko Uruñuela
2023 — conf
A deep learning-based approach to increase efficiency in the acquisition of ultrasonic non-destructive testing datasets.
CVPR Workshops
Nick Luiken, Matteo Ravasi
2023 J jnl
Explainable Artificial Intelligence driven mask design for self-supervised seismic denoising.
CoRR
Claire Birnie, Matteo Ravasi
2023 J jnl
IntraSeismic: a coordinate-based learning approach to seismic inversion.
CoRR
Juan Romero, Wolfgang Heidrich, Nick Luiken, Matteo Ravasi
2023 J jnl
PINNslope: seismic data interpolation and local slope estimation with physics informed neural networks.
CoRR
Francesco Brandolin, Matteo Ravasi, Tariq Alkhalifah
2023 A conf
Scaling the "Memory Wall" for Multi-Dimensional Seismic Processing with Algebraic Compression on Cerebras CS-2 Systems.
SC
Hatem Ltaief, Yuxi Hong, Leighton Wilson, Mathias Jacquelin, Matteo Ravasi, David Elliot Keyes
2023 C conf
Steering Customized AI Architectures for HPC Scientific Applications.
ISC
Hatem Ltaief, Yuxi Hong, Adel Dabah, Rabab Alomairy, Sameh Abdulah, Chris Goreczny, Pawel Gepner, Matteo Ravasi, Damien Gratadour, David E. Keyes
2022 J jnl
A hybrid approach to seismic deblending: when physics meets self-supervision.
CoRR
Nick Luiken, Matteo Ravasi, Claire E. Birnie
2022 J jnl
Deep Preconditioners and their application to seismic wavefield processing.
CoRR
Matteo Ravasi
2022 J jnl
Intelligent Seismic Deblending Through Deep Preconditioner.
IEEE Geosci. Remote. Sens. Lett.
Weiwei Xu, Vincenzo Lipari, Paolo Bestagini, Matteo Ravasi, Wenchao Chen, Stefano Tubaro
2022 J jnl
Posterior sampling with CNN-based, Plug-and-Play regularization with applications to Post-Stack Seismic Inversion.
CoRR
Muhammad Izzatullah, Tariq Alkhalifah, Juan Romero, Miguel Corrales, Nick Luiken, Matteo Ravasi
2022 J jnl
Responsibly Reckless Matrix Algorithms for HPC Scientific Applications.
Comput. Sci. Eng.
Hatem Ltaief, Marc G. Genton, Damien Gratadour, David E. Keyes, Matteo Ravasi
2022 J jnl
Stochastic Multi-Dimensional Deconvolution.
IEEE Trans. Geosci. Remote. Sens.
Matteo Ravasi, Tamin Selvan, Nick Luiken
2021 J jnl
Accelerating Seismic Redatuming Using Tile Low-Rank Approximations on NEC SX-Aurora TSUBASA.
Supercomput. Front. Innov.
Yuxi Hong, Hatem Ltaief, Matteo Ravasi, Laurent Gatineau, David E. Keyes
2021 J jnl
The potential of self-supervised networks for random noise suppression in seismic data.
CoRR
Claire Birnie, Matteo Ravasi, Tariq Alkhalifah, Sixiu Liu
2021 J jnl
Time-Domain Multidimensional Deconvolution: A Physically Reliable and Stable Preconditioned Implementation.
Remote. Sens.
David Vargas, Ivan Vasconcelos, Matteo Ravasi, Nick Luiken
2020 J jnl
On the implementation of large-scale integral operators with modern HPC solutions - Application to 3D Marchenko imaging by least-squares inversion.
CoRR
Matteo Ravasi, Ivan Vasconcelos
2020 J jnl
PyLops - A linear-operator Python library for scalable algebra and optimization.
SoftwareX
Matteo Ravasi, Ivan Vasconcelos
2019 J jnl
PyLops - A Linear-Operator Python Library for large scale optimization.
CoRR
Matteo Ravasi, Ivan Vasconcelos