Tatiana A. Bubba

20 papers Journal 15Unranked 3

Year	Rank	Type	Title / 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