Matteo Ravasi

Orcid: 0000-0003-0020-2721

According to our database1, Matteo Ravasi authored at least 20 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
PyProximal - scalable convex optimization in Python.
J. Open Source Softw., April, 2024

Multidimensional deconvolution with shared bases.
CoRR, 2024

2023
IntraSeismic: a coordinate-based learning approach to seismic inversion.
CoRR, 2023

Explainable Artificial Intelligence driven mask design for self-supervised seismic denoising.
CoRR, 2023

PINNslope: seismic data interpolation and local slope estimation with physics informed neural networks.
CoRR, 2023

Steering Customized AI Architectures for HPC Scientific Applications.
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.
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.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022
Stochastic Multi-Dimensional Deconvolution.
IEEE Trans. Geosci. Remote. Sens., 2022

Intelligent Seismic Deblending Through Deep Preconditioner.
IEEE Geosci. Remote. Sens. Lett., 2022

Responsibly Reckless Matrix Algorithms for HPC Scientific Applications.
Comput. Sci. Eng., 2022

Posterior sampling with CNN-based, Plug-and-Play regularization with applications to Post-Stack Seismic Inversion.
CoRR, 2022

Deep Preconditioners and their application to seismic wavefield processing.
CoRR, 2022

A hybrid approach to seismic deblending: when physics meets self-supervision.
CoRR, 2022

2021
Accelerating Seismic Redatuming Using Tile Low-Rank Approximations on NEC SX-Aurora TSUBASA.
Supercomput. Front. Innov., 2021

Time-Domain Multidimensional Deconvolution: A Physically Reliable and Stable Preconditioned Implementation.
Remote. Sens., 2021

The potential of self-supervised networks for random noise suppression in seismic data.
CoRR, 2021

2020
PyLops - A linear-operator Python library for scalable algebra and optimization.
SoftwareX, 2020

On the implementation of large-scale integral operators with modern HPC solutions - Application to 3D Marchenko imaging by least-squares inversion.
CoRR, 2020

2019
PyLops - A Linear-Operator Python Library for large scale optimization.
CoRR, 2019


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