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Riccardo Barbano
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Year
Quantifying Model Uncertainty in Inverse Problems via Bayesian Deep Gradient Descent
R Barbano, C Zhang, S Arridge, B Jin
2020 25th International Conference on Pattern Recognition (ICPR), 1392-1399, 2020
82020
Unsupervised Knowledge-Transfer for Learned Image Reconstruction
R Barbano, Z Kereta, A Hauptmann, SR Arridge, B Jin
arXiv preprint arXiv:2107.02572, 2021
32021
Quantifying Sources of Uncertainty in Deep Learning-Based Image Reconstruction
R Barbano, Ž Kereta, C Zhang, A Hauptmann, S Arridge, B Jin
NeurIPS 2020 Workshop on Deep Learning and Inverse Problems, 2020
32020
A Probabilistic Deep Image Prior over Image Space
R Barbano, J Antoran, JM Hernández-Lobato, B Jin
Fourth Symposium on Advances in Approximate Bayesian Inference, 2021
22021
Conditional Variational Autoencoder for Learned Image Reconstruction
C Zhang, R Barbano, B Jin
Computation 9 (11), 114, 2021
22021
Is Deep Image Prior in Need of a Good Education?
R Barbano, J Leuschner, M Schmidt, A Denker, A Hauptmann, P Maaß, ...
arXiv preprint arXiv:2111.11926, 2021
12021
Adapting the Linearised Laplace Model Evidence for Modern Deep Learning
J Antorán, D Janz, JU Allingham, E Daxberger, R Barbano, E Nalisnick, ...
arXiv preprint arXiv:2206.08900, 2022
2022
Uncertainty quantification in medical image synthesis
B Jin, R Barbano, S Arridge, R Tanno
Elsevier, 2022
2022
A Probabilistic Deep Image Prior for Computational Tomography
J Antorán, R Barbano, J Leuschner, JM Hernández-Lobato, B Jin
arXiv preprint arXiv:2203.00479, 2022
2022
Investigating Inference in Bayesian Neural Networks via Active Learning
R Barbano, J Gordon, R Pinsler, JM Hernández-Lobato
Variational Continual Learning in Deep Discriminative Models
G Bae, R Barbano, J Bunker
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Articles 1–11