Matthieu Terris
Github · Google Scholar · Linkedin
Github · Google Scholar · Linkedin
I am currently a postdoctoral researcher within the MIND team at INRIA, working on ML techniques for EEG data,
data augmentation and inverse problems. I obtained my PhD from the Biomedical and Astronomical Signal Processing (BASP) laboratory
at Heriot-Watt University, Edinburgh, UK under the supervision
of Prof. Yves Wiaux and Prof. Jean-Christophe Pesquet.
Feel free to reach me by email :)
Contact: matthieu.terris@gmail.com
Software
| DeepInverse |
A torch-based library for solving inverse problems, joint work with Dongdong, Samuel and Julian.
Check it out! [github] [doc] |
Preprints
| 2023 |
Equivariant plug-and-play image reconstruction,
Matthieu Terris*, Thomas Moreau, Nelly Pustelnik, Julian Tachella arxiv [PDF] |
| 2023 |
Meta-Prior: Meta learning for Adaptive Inverse Problem Solvers,
Matthieu Terris*, Thomas Moreau arxiv [PDF] |
| 2023 |
Plug-and-play imaging with model uncertainty quantification in radio astronomy,
Matthieu Terris*, Chao Tang*, Adrian Jackson, Yves Wiaux arxiv [PDF] |
Published or Accepted Journal Articles
| 2023 |
Scalable precision wide-field imaging in radio interferometry–II. AIRI validated on ASKAP data,
Amanda Wilber*, Arwa Dabbech, Matthieu Terris, Adrian Jackson, Yves Wiaux Monthly Notices of the Royal Astronomy Society, 2023 [PDF] |
| 2022 |
First AI for deep super-resolution wide-field imaging in radio astronomy: unveiling structure in ESO 137-006,
Arwa Dabbech*, Matthieu Terris, Adrian Jackson, Mpati Ramatsoku, Oleg M Smirnov, Yves Wiaux The Astrophysical Journal Letters, 2023 [PDF] |
| 2022 |
Image reconstruction algorithms in radio interferometry: from handcrafted to learned regularization denoisers,
Matthieu Terris*, Arwa Dabbech, Chao Tang, Yves Wiaux Monthly Notices of the Royal Astronomical Society, 2022 [PDF] [Code (coming soon)] |
| 2021 |
Learning Maximally Monotone Operators for Image Recovery,
Jean-Christophe Pesquet, Audrey Repetti*, Matthieu Terris*, Yves Wiaux SIAM Journal on Imaging Sciences, 2021 [PDF] [Code] |
| 2020 |
Integrating deep learning CT-scan model, biological and clinical variables to predict severity of COVID-19 patients,
Nathalie Lassau, Samy Ammari, Emilie Chouzenoux, ..., Matthieu Terris, ..., et al Nature Communications, 2021 [PDF] [Code] |
Conference Proceedings
| 2023 |
Investigating Model Robustness Against Sensor Variation,
Matthieu Terris*, Sagar Verma IGARSS 2023. [PDF] |
| 2023 |
Have Foundational Models Seen Satellite Images?,
PanigrahiMatthieu Terris*, Sagar Verma IGARSS 2023. [PDF] |
| 2022 |
Deep network series for large-scale high-dynamic range imaging,
Amir Aghabiglou*, Matthieu Terris*, Adrian Jackson, Yves Wiaux ICASSP 2023. [PDF] |
| 2022 |
Dual Forward-Backward Unfolded Network for Flexible Plug-and-Play,
Audrey Repetti*, Matthieu Terris, Jean-Christophe Pesquet, Yves Wiaux EUSIPCO 2022. [PDF] [Code (coming soon!)] |
| 2021 |
Enhanced Convergent PnP Algorithms For Image Restoration,
Matthieu Terris*, Audrey Repetti, Jean-Christophe Pesquet, Yves Wiaux ICIP 2021 [PDF] |
| 2020 |
Building Firmly Nonexpansive Convolutional Neural Networks,
Matthieu Terris*, Audrey Repetti, Jean-Christophe Pesquet, Yves Wiaux ICASSP 2020 [PDF] |
| 2019 |
Deep Post Processing for Sparse Image Deconvolution,
Matthieu Terris*, Abdullah Abdulaziz, Arwa Dabbech, Ming Jiang, Audrey Repetti, Jean-Christophe Pesquet, Yves Wiaux SPARS 2019 [PDF] |
| 2019 |
Stochastic MM Subspace Algorithms,
Matthieu Terris, Emilie Chouzenoux BASP 2019 [PDF] |
* denotes equal contribution/corresponding author.
PhD Thesis
| 2022 |
Learning priors for scalable computational imaging algorithms, from theory to application in radio astronomy
Heriot-Watt University, 2022. [PDF] |