| Probabilistic Watershed: Sampling all spanning forests for seeded segmentation and semi-supervised learning E Fita Sanmartín, S Damrich, FA Hamprecht NeurIPS2019, 2019 | 5 | 2019 |
| Theory and approximate solvers for branched optimal transport with multiple sources P Lippmann, E Fita Sanmartín, FA Hamprecht Advances in Neural Information Processing Systems 35, 267-279, 2022 | 4 | 2022 |
| The algebraic path problem for graph metrics E Fita Sanmartın, S Damrich, F Hamprecht International Conference on Machine Learning, 19178-19204, 2022 | 2 | 2022 |
| Directed probabilistic watershed E Fita Sanmartin, S Damrich, FA Hamprecht Advances in Neural Information Processing Systems 34, 20076-20088, 2021 | 2 | 2021 |
| The Central Spanning Tree Problem E Fita Sanmartín, C Schnörr, FA Hamprecht | | 2024 |
| Extensions of Karger's Algorithm: Why They Fail in Theory and How They Are Useful in Practice E Jenner, E Fita Sanmartín, FA Hamprecht Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | | 2021 |
