Tatiana A. Bubba

20 papers Journal 15Unranked 3
YearRankTypeTitle / Venue / Authors
2025 — conf
Fast Inexact Bilevel Optimization for Analytical Deep Image Priors.
SSVM (1)
Mohammad Sadegh Salehi, Tatiana A. Bubba, Yury Korolev
2025 J jnl
Fast Inexact Bilevel Optimization for Analytical Deep Image Priors.
CoRR
Mohammad Sadegh Salehi, Tatiana A. Bubba, Yury Korolev
2025 J jnl
Regularization with Optimal Space-Time Priors.
SIAM J. Imaging Sci.
Tatiana A. Bubba, Tommi Heikkilä, Demetrio Labate, Luca Ratti
2025 J jnl
Revisiting ΨDONet: microlocally inspired filters for incomplete-data tomographic reconstructions.
CoRR
Tatiana A. Bubba, Luca Ratti, Andrea Sebastiani
2025 — ed.
Scale Space and Variational Methods in Computer Vision - 10th International Conference, SSVM 2025, Dartington, UK, May 18-22, 2025, Proceedings, Part I
SSVM (1)
Tatiana A. Bubba, Romina Gaburro, Silvia Gazzola, Kostas Papafitsoros, Marcelo Pereyra, Carola-Bibiane Schönlieb
2025 — ed.
Scale Space and Variational Methods in Computer Vision - 10th International Conference, SSVM 2025, Dartington, UK, May 18-22, 2025, Proceedings, Part II
SSVM (2)
Tatiana A. Bubba, Romina Gaburro, Silvia Gazzola, Kostas Papafitsoros, Marcelo Pereyra, Carola-Bibiane Schönlieb
2025 J jnl
TomoSelfDEQ: Self-Supervised Deep Equilibrium Learning for Sparse-Angle CT Reconstruction.
CoRR
Tatiana A. Bubba, Matteo Santacesaria, Andrea Sebastiani
2025 — conf
TomoSelfDEQ: Self-supervised Deep Equilibrium Learning for Sparse-Angle CT Reconstruction.
SSVM (1)
Tatiana A. Bubba, Matteo Santacesaria, Andrea Sebastiani
2024 J jnl
Regularization with optimal space-time priors.
CoRR
Tatiana A. Bubba, Tommi Heikkilä, Demetrio Labate, Luca Ratti
2023 J jnl
Bilevel learning of regularization models and their discretization for image deblurring and super-resolution.
CoRR
Tatiana A. Bubba, Luca Calatroni, Ambra Catozzi, Serena Crisci, Thomas Pock, Monica Pragliola, Siiri Rautio, Danilo Riccio, Andrea Sebastiani
2023 J jnl
Efficient representation of spatio-temporal data using cylindrical shearlets.
J. Comput. Appl. Math.
Tatiana A. Bubba, Glenn R. Easley, Tommi Heikkilä, Demetrio Labate, Jose P. Rodriguez Ayllon
2023 J jnl
Trust your source: quantifying source condition elements for variational regularisation methods.
CoRR
Martin Benning, Tatiana A. Bubba, Luca Ratti, Danilo Riccio
2021 — conf
4D Dual-Tree Complex Wavelets for Time-Dependent Data.
ICCSA (Workshops)
Tatiana A. Bubba, Tommi Heikkilä, Samuli Siltanen
2021 J jnl
4D Dual-Tree Complex Wavelets for Time-Dependent Data.
CoRR
Tatiana A. Bubba, Tommi Heikkilä, Samuli Siltanen
2021 J jnl
Convex regularization in statistical inverse learning problems.
CoRR
Tatiana A. Bubba, Martin Burger, Tapio Helin, Luca Ratti
2021 J jnl
Deep Neural Networks for Inverse Problems with Pseudodifferential Operators: An Application to Limited-Angle Tomography.
SIAM J. Imaging Sci.
Tatiana A. Bubba, Mathilde Galinier, Matti Lassas, Marco Prato, Luca Ratti, Samuli Siltanen
2020 J jnl
Deep neural networks for inverse problems with pseudodifferential operators: an application to limited-angle tomography.
CoRR
Tatiana A. Bubba, Mathilde Galinier, Matti Lassas, Marco Prato, Luca Ratti, Samuli Siltanen
2020 J jnl
Sparse dynamic tomography. A shearlet-based approach for iodine perfusion in plant stems.
CoRR
Tatiana A. Bubba, Tommi Heikkilä, Hanna Help, Simo Huotari, Yann Salmon, Samuli Siltanen
2018 J jnl
A nonsmooth regularization approach based on shearlets for Poisson noise removal in ROI tomography.
Appl. Math. Comput.
Tatiana A. Bubba, Federica Porta, Gaetano Zanghirati, Silvia Bonettini
2018 J jnl
Learning The Invisible: A Hybrid Deep Learning-Shearlet Framework for Limited Angle Computed Tomography.
CoRR
Tatiana A. Bubba, Gitta Kutyniok, Matti Lassas, Maximilian März, Wojciech Samek, Samuli Siltanen, Vignesh Srinivasan