Riccardo Barbano

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 22

Top Topics

Sparsely Sampled

Computed Tomography

Top Venues

Trans. Mach. Learn. Res.

IEEE Trans. Computational Imaging

Publications

Riccardo Barbano, Javier Antorán, Johannes Leuschner, José Miguel Hernández-Lobato, Bangti Jin, Zeljko Kereta
Image Reconstruction via Deep Image Prior Subspaces. Trans. Mach. Learn. Res. 2024 (2024)
Alexander Denker, Francisco Vargas, Shreyas Padhy, Kieran Didi, Simon V. Mathis, Vincent Dutordoir, Riccardo Barbano, Emile Mathieu, Urszula Julia Komorowska, Pietro Lio
DEFT: Efficient Finetuning of Conditional Diffusion Models by Learning the Generalised h-transform. CoRR (2024)
Imraj RD Singh, Alexander Denker, Riccardo Barbano, Zeljko Kereta, Bangti Jin, Kris Thielemans, Peter Maass, Simon R. Arridge
Score-Based Generative Models for PET Image Reconstruction. CoRR (2023)
Marco Nittscher, Michael Lameter, Riccardo Barbano, Johannes Leuschner, Bangti Jin, Peter Maass
SVD-DIP: Overcoming the Overfitting Problem in DIP-based CT Reconstruction. CoRR (2023)
Javier Antorán, Riccardo Barbano, Johannes Leuschner, José Miguel Hernández-Lobato, Bangti Jin
Uncertainty Estimation for Computed Tomography with a Linearised Deep Image Prior. Trans. Mach. Learn. Res. 2023 (2023)
Marco Nittscher, Michael Falk Lameter, Riccardo Barbano, Johannes Leuschner, Bangti Jin, Peter Maass
SVD-DIP: Overcoming the Overfitting Problem in DIP-based CT Reconstruction. MIDL (2023)
Javier Antorán, Shreyas Padhy, Riccardo Barbano, Eric T. Nalisnick, David Janz, José Miguel Hernández-Lobato
Sampling-based inference for large linear models, with application to linearised Laplace. ICLR (2023)
Riccardo Barbano, Alexander Denker, Hyungjin Chung, Tae-Hoon Roh, Simon Arrdige, Peter Maass, Bangti Jin, Jong Chul Ye
Steerable Conditional Diffusion for Out-of-Distribution Adaptation in Imaging Inverse Problems. CoRR (2023)
Riccardo Barbano, Javier Antorán, Johannes Leuschner, José Miguel Hernández-Lobato, Zeljko Kereta, Bangti Jin
Fast and Painless Image Reconstruction in Deep Image Prior Subspaces. CoRR (2023)
Riccardo Barbano, Johannes Leuschner, Maximilian Schmidt, Alexander Denker, Andreas Hauptmann, Peter Maass, Bangti Jin
An Educated Warm Start for Deep Image Prior-Based Micro CT Reconstruction. IEEE Trans. Computational Imaging 8 (2022)
Javier Antorán, Riccardo Barbano, Johannes Leuschner, José Miguel Hernández-Lobato, Bangti Jin
A Probabilistic Deep Image Prior for Computational Tomography. CoRR (2022)
Javier Antorán, David Janz, James Urquhart Allingham, Erik A. Daxberger, Riccardo Barbano, Eric T. Nalisnick, José Miguel Hernández-Lobato
Adapting the Linearised Laplace Model Evidence for Modern Deep Learning. CoRR (2022)
Javier Antorán, Shreyas Padhy, Riccardo Barbano, Eric T. Nalisnick, David Janz, José Miguel Hernández-Lobato
Sampling-based inference for large linear models, with application to linearised Laplace. CoRR (2022)
Javier Antorán, David Janz, James Urquhart Allingham, Erik A. Daxberger, Riccardo Barbano, Eric T. Nalisnick, José Miguel Hernández-Lobato
Adapting the Linearised Laplace Model Evidence for Modern Deep Learning. ICML (2022)
Riccardo Barbano, Johannes Leuschner, Javier Antorán, Bangti Jin, José Miguel Hernández-Lobato
Bayesian Experimental Design for Computed Tomography with the Linearised Deep Image Prior. CoRR (2022)
Riccardo Barbano, Johannes Leuschner, Maximilian Schmidt, Alexander Denker, Andreas Hauptmann, Peter Maaß, Bangti Jin
Is Deep Image Prior in Need of a Good Education? CoRR (2021)
Riccardo Barbano, Zeljko Kereta, Andreas Hauptmann, Simon R. Arridge, Bangti Jin
Unsupervised Knowledge-Transfer for Learned Image Reconstruction. CoRR (2021)
Chen Zhang, Riccardo Barbano, Bangti Jin
Conditional Variational Autoencoder for Learned Image Reconstruction. CoRR (2021)
Chen Zhang, Riccardo Barbano, Bangti Jin
Conditional Variational Autoencoder for Learned Image Reconstruction. Comput. 9 (11) (2021)
Riccardo Barbano, Chen Zhang, Simon R. Arridge, Bangti Jin
Quantifying Model Uncertainty in Inverse Problems via Bayesian Deep Gradient Descent. ICPR (2020)
Riccardo Barbano, Zeljko Kereta, Chen Zhang, Andreas Hauptmann, Simon R. Arridge, Bangti Jin
Quantifying Sources of Uncertainty in Deep Learning-Based Image Reconstruction. CoRR (2020)
Riccardo Barbano, Chen Zhang, Simon R. Arridge, Bangti Jin
Quantifying Model Uncertainty in Inverse Problems via Bayesian Deep Gradient Descent. CoRR (2020)