Matteo Ravasi

According to our database, Matteo Ravasi authored at least 21 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

PyProximal - scalable convex optimization in Python.

Matteo Ravasi, Marcus Valtonen Örnhag, Nick Luiken, Olivier Leblanc, Eneko Uruñuela

J. Open Source Softw., April, 2024

High performance computing seismic redatuming by inversion with algebraic compression and multiple precisions.

Yuxi Hong, Hatem Ltaief, Matteo Ravasi, David E. Keyes

Int. J. High Perform. Comput. Appl., 2024

Multidimensional deconvolution with shared bases.

Daria Sushnikova, Matteo Ravasi, David E. Keyes

CoRR, 2024

2023

IntraSeismic: a coordinate-based learning approach to seismic inversion.

Juan Romero, Wolfgang Heidrich, Nick Luiken, Matteo Ravasi

CoRR, 2023

Explainable Artificial Intelligence driven mask design for self-supervised seismic denoising.

Claire Birnie, Matteo Ravasi

CoRR, 2023

PINNslope: seismic data interpolation and local slope estimation with physics informed neural networks.

Francesco Brandolin, Matteo Ravasi, Tariq Alkhalifah

CoRR, 2023

Steering Customized AI Architectures for HPC Scientific Applications.

Hatem Ltaief, Yuxi Hong, Adel Dabah, Rabab Alomairy, Sameh Abdulah, Chris Goreczny, Pawel Gepner, Matteo Ravasi, Damien Gratadour, David E. Keyes

Proceedings of the High Performance Computing - 38th International Conference, 2023

Scaling the "Memory Wall" for Multi-Dimensional Seismic Processing with Algebraic Compression on Cerebras CS-2 Systems.

Hatem Ltaief, Yuxi Hong, Leighton Wilson, Mathias Jacquelin, Matteo Ravasi, David Elliot Keyes

Proceedings of the International Conference for High Performance Computing, 2023

A deep learning-based approach to increase efficiency in the acquisition of ultrasonic non-destructive testing datasets.

Nick Luiken, Matteo Ravasi

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

Stochastic Multi-Dimensional Deconvolution.

Matteo Ravasi, Tamin Selvan, Nick Luiken

IEEE Trans. Geosci. Remote. Sens., 2022

Intelligent Seismic Deblending Through Deep Preconditioner.

Weiwei Xu, Vincenzo Lipari, Paolo Bestagini, Matteo Ravasi, Wenchao Chen, Stefano Tubaro

IEEE Geosci. Remote. Sens. Lett., 2022

Responsibly Reckless Matrix Algorithms for HPC Scientific Applications.

Hatem Ltaief, Marc G. Genton, Damien Gratadour, David E. Keyes, Matteo Ravasi

Comput. Sci. Eng., 2022

Posterior sampling with CNN-based, Plug-and-Play regularization with applications to Post-Stack Seismic Inversion.

Muhammad Izzatullah, Tariq Alkhalifah, Juan Romero, Miguel Corrales, Nick Luiken, Matteo Ravasi

CoRR, 2022

Deep Preconditioners and their application to seismic wavefield processing.

Matteo Ravasi

CoRR, 2022

A hybrid approach to seismic deblending: when physics meets self-supervision.

Nick Luiken, Matteo Ravasi, Claire E. Birnie

CoRR, 2022

2021

Accelerating Seismic Redatuming Using Tile Low-Rank Approximations on NEC SX-Aurora TSUBASA.

Yuxi Hong, Hatem Ltaief, Matteo Ravasi, Laurent Gatineau, David E. Keyes

Supercomput. Front. Innov., 2021

Time-Domain Multidimensional Deconvolution: A Physically Reliable and Stable Preconditioned Implementation.

David Vargas, Ivan Vasconcelos, Matteo Ravasi, Nick Luiken

Remote. Sens., 2021

The potential of self-supervised networks for random noise suppression in seismic data.

Claire Birnie, Matteo Ravasi, Tariq Alkhalifah, Sixiu Liu

CoRR, 2021

2020

PyLops - A linear-operator Python library for scalable algebra and optimization.

Matteo Ravasi, Ivan Vasconcelos

SoftwareX, 2020

On the implementation of large-scale integral operators with modern HPC solutions - Application to 3D Marchenko imaging by least-squares inversion.

Matteo Ravasi, Ivan Vasconcelos

CoRR, 2020

2019

PyLops - A Linear-Operator Python Library for large scale optimization.

Matteo Ravasi, Ivan Vasconcelos

CoRR, 2019