293 citations · 1.8k across the 110 of their papers we have counts for
5 papers · 1 filter
Image Reconstruction via Deep Image Prior Subspaces
Riccardo Barbano, Javier Antorán, Johannes Leuschner +3
Deep learning has been widely used for solving image reconstruction tasks but its deployability has been held back due to the shortage of high-quality training data. Unsupervised l…
Bayesian Experimental Design for Computed Tomography with the Linearised Deep Image Prior
Riccardo Barbano, Johannes Leuschner, Javier Antorán +2
We investigate adaptive design based on a single sparse pilot scan for generating effective scanning strategies for computed tomography reconstruction. We propose a novel approach…
Conditional Variational Autoencoder for Learned Image Reconstruction
Chen Zhang, Riccardo Barbano, Bangti Jin
Learned image reconstruction techniques using deep neural networks have recently gained popularity, and have delivered promising empirical results. However, most approaches focus o…
Quantifying Sources of Uncertainty in Deep Learning-Based Image Reconstruction
Riccardo Barbano, Željko Kereta, Chen Zhang +3
Image reconstruction methods based on deep neural networks have shown outstanding performance, equalling or exceeding the state-of-the-art results of conventional approaches, but o…
Quantifying Model Uncertainty in Inverse Problems via Bayesian Deep Gradient Descent
Riccardo Barbano, Chen Zhang, Simon Arridge +1
Recent advances in reconstruction methods for inverse problems leverage powerful data-driven models, e.g., deep neural networks. These techniques have demonstrated state-of-the-art…