| Recurrent Inference Machines for Solving Inverse Problems P Putzky, M Welling arXiv preprint arXiv:1706.04008, 2017 | 63 | 2017 |
| Invert to learn to invert P Putzky, M Welling arXiv preprint arXiv:1911.10914, 2019 | 34 | 2019 |
| Data-driven reconstruction of gravitationally lensed galaxies using recurrent inference machines WR Morningstar, LP Levasseur, YD Hezaveh, R Blandford, P Marshall, ... The Astrophysical Journal 883 (1), 14, 2019 | 25 | 2019 |
| Recurrent Inference Machines for Reconstructing Heterogeneous MRI Data K Lønning, P Putzky, JJ Sonke, L Reneman, MWA Caan, M Welling Medical Image Analysis 53, 64-78, 2019 | 24 | 2019 |
| Recurrent inference machines for accelerated MRI reconstruction K Lønning, P Putzky, MWA Caan, M Welling | 14 | 2018 |
| Analyzing interferometric observations of strong gravitational lenses with recurrent and convolutional neural networks WR Morningstar, YD Hezaveh, LP Levasseur, RD Blandford, PJ Marshall, ... arXiv preprint arXiv:1808.00011, 2018 | 9 | 2018 |
| A Bayesian model for identifying hierarchically organised states in neural population activity P Putzky, F Franzen, G Bassetto Advances in Neural Information Processing Systems 27: 28th Annual Conference …, 2015 | 8 | 2015 |
| i-RIM applied to the fastMRI challenge P Putzky, D Karkalousos, J Teuwen, N Miriakov, B Bakker, M Caan, ... arXiv preprint arXiv:1910.08952, 2019 | 7 | 2019 |
| Reconstructing missing seismic data using Deep Learning D Kuijpers, I Vasconcelos, P Putzky arXiv preprint arXiv:2101.09554, 2021 | | 2021 |
| Reconstructing Missing Seismic Data through Deep Learning with Recurrent Inference Machines D Kuijpers, I Vasconcelos, P Putzky EAGE 2020 Annual Conference & Exhibition Online 2020 (1), 1-5, 2020 | | 2020 |
| Towards highly-sparse, autonomous imaging systems: high-resolution wavefield imaging for frontier exploration I Vasconcelos, J Ruan, D Kuijpers, M Ravasi, P Putzky EGU General Assembly Conference Abstracts, 18782, 2020 | | 2020 |
