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2020 – today
- 2024
[j4]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)- [i15]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 abs/2406.01781 (2024) - [i14]Victor Sabanza Gil, Riccardo Barbano, Daniel Pacheco Gutiérrez, Jeremy S. Luterbacher, José Miguel Hernández-Lobato, Philippe Schwaller, Loïc Roch:
Best Practices for Multi-Fidelity Bayesian Optimization in Materials and Molecular Research. CoRR abs/2410.00544 (2024) - 2023
- [j3]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) - [c4]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 - [c3]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: 617-642 - [i13]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 abs/2302.10279 (2023) - [i12]Marco Nittscher, Michael Lameter, Riccardo Barbano, Johannes Leuschner, Bangti Jin, Peter Maass:
SVD-DIP: Overcoming the Overfitting Problem in DIP-based CT Reconstruction. CoRR abs/2303.15748 (2023) - [i11]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 abs/2308.14190 (2023) - [i10]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 abs/2308.14409 (2023) - 2022
- [j2]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: 1210-1222 (2022) - [c2]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: 796-821 - [i9]Javier Antorán, Riccardo Barbano, Johannes Leuschner, José Miguel Hernández-Lobato, Bangti Jin:
A Probabilistic Deep Image Prior for Computational Tomography. CoRR abs/2203.00479 (2022) - [i8]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 abs/2206.08900 (2022) - [i7]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 abs/2207.05714 (2022) - [i6]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 abs/2210.04994 (2022) - 2021
- [j1]Chen Zhang, Riccardo Barbano, Bangti Jin:
Conditional Variational Autoencoder for Learned Image Reconstruction. Comput. 9(11): 114 (2021) - [i5]Riccardo Barbano, Zeljko Kereta, Andreas Hauptmann, Simon R. Arridge, Bangti Jin:
Unsupervised Knowledge-Transfer for Learned Image Reconstruction. CoRR abs/2107.02572 (2021) - [i4]Chen Zhang, Riccardo Barbano, Bangti Jin:
Conditional Variational Autoencoder for Learned Image Reconstruction. CoRR abs/2110.11681 (2021) - [i3]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 abs/2111.11926 (2021) - 2020
- [c1]Riccardo Barbano, Chen Zhang, Simon R. Arridge, Bangti Jin:
Quantifying Model Uncertainty in Inverse Problems via Bayesian Deep Gradient Descent. ICPR 2020: 1392-1399 - [i2]Riccardo Barbano, Chen Zhang, Simon R. Arridge, Bangti Jin:
Quantifying Model Uncertainty in Inverse Problems via Bayesian Deep Gradient Descent. CoRR abs/2007.09971 (2020) - [i1]Riccardo Barbano, Zeljko Kereta, Chen Zhang, Andreas Hauptmann, Simon R. Arridge, Bangti Jin:
Quantifying Sources of Uncertainty in Deep Learning-Based Image Reconstruction. CoRR abs/2011.08413 (2020)
Coauthor Index
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