| Adapting the Linearised Laplace Model Evidence for Modern Deep Learning J Antorán, D Janz, JU Allingham, E Daxberger, RR Barbano, E Nalisnick, ... International Conference on Machine Learning, 796-821, 2022 | 26 | 2022 |
| An Educated Warm Start For Deep Image Prior-Based Micro CT Reconstruction R Barbano, J Leuschner, M Schmidt, A Denker, A Hauptmann, P Maaß, ... IEEE Transactions on Computational Imaging 8, 1210-1222, 2022 | 21* | 2022 |
| 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 | 19 | 2020 |
| Uncertainty quantification in medical image synthesis R Barbano, S Arridge, B Jin, R Tanno Biomedical Image Synthesis and Simulation, 601-641, 2022 | 18 | 2022 |
| Conditional Variational Autoencoder for Learned Image Reconstruction C Zhang, R Barbano, B Jin Computation 9 (11), 114, 2021 | 16 | 2021 |
| Sampling-based inference for large linear models, with application to linearised Laplace J Antorán, S Padhy, R Barbano, E Nalisnick, D Janz, ... International Conference on Learning Representations (ICLR), 2023, 2022 | 15 | 2022 |
| Uncertainty Estimation for Computed Tomography with a Linearised Deep Image Prior J Antorán, R Barbano, J Leuschner, JM Hernández-Lobato, B Jin Transactions on Machine Learning Research (12/2023), 2022 | 12* | 2022 |
| 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 | 10 | 2020 |
| Unsupervised Knowledge-Transfer for Learned Image Reconstruction R Barbano, Z Kereta, A Hauptmann, SR Arridge, B Jin Inverse Problems 38 (10), 104004, 2022 | 8 | 2022 |
| Bayesian Experimental Design for Computed Tomography with the Linearised Deep Image Prior R Barbano, J Leuschner, J Antorán, B Jin, JM Hernández-Lobato Adaptive Experimental Design and Active Learning workshop at ICML 2022, 2022 | 8 | 2022 |
| Steerable conditional diffusion for out-of-distribution adaptation in imaging inverse problems R Barbano, A Denker, H Chung, TH Roh, S Arrdige, P Maass, B Jin, ... arXiv preprint arXiv:2308.14409, 2023 | 6 | 2023 |
| SVD-DIP: Overcoming the Overfitting Problem in DIP-based CT Reconstruction M Nittscher, M Lameter, R Barbano, J Leuschner, B Jin, P Maass Medical Imaging with Deep Learning, 2023, 2023 | 4 | 2023 |
| Image Reconstruction via Deep Image Prior Subspaces R Barbano, J Antorán, J Leuschner, JM Hernández-Lobato, Ž Kereta, ... Transactions on Machine Learning Research (1/2024), 2023 | 4* | 2023 |
| A Probabilistic Deep Image Prior over Image Space R Barbano, J Antorán, JM Hernández-Lobato, B Jin Fourth Symposium on Advances in Approximate Bayesian Inference, 2022 | 4 | 2022 |
| Score-based generative models for PET image reconstruction IRD Singh, A Denker, R Barbano, Ž Kereta, B Jin, K Thielemans, P Maass, ... arXiv preprint arXiv:2308.14190, 2023 | 3 | 2023 |
| 3D PET-DIP reconstruction with relative difference prior using a SIRF-based objective I Singh, R Barbano, Z Kereta, B Jin, K Thielemans, S Arridge Fully3D, 2023 | 1 | 2023 |
| Deep Image Prior PET Reconstruction using a SIRF-Based Objective IRD Singh, R Barbano, R Twyman, Ž Kereta, B Jin, S Arridge, ... 2022 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC …, 2022 | 1 | 2022 |
| DEFT: Efficient Finetuning of Conditional Diffusion Models by Learning the Generalised -transform A Denker, F Vargas, S Padhy, K Didi, S Mathis, V Dutordoir, R Barbano, ... arXiv preprint arXiv:2406.01781, 2024 | | 2024 |
| Scalable Uncertainty Quantification and Learning for Deep Computed Tomography Reconstruction R Barbano UCL (University College London), 2024 | | 2024 |
| MR-blob: Coordinate-Transformed Blobs for Parallel MRI Reconstruction Z Kereta, A Denker, R Barbano, B Jin, K Thielemans, S Arrdige, I Singh | | 2024 |
Bangti JinDepartment of Mathematics, The Chinese University of Hong Kong在 math.cuhk.edu.hk 的电子邮件经过验证
