| Avoiding discrimination through causal reasoning N Kilbertus, M Rojas Carulla, G Parascandolo, M Hardt, D Janzing, ... Advances in neural information processing systems 30, 2017 | 485 | 2017 |
| Invariant models for causal transfer learning M Rojas-Carulla, B Schölkopf, R Turner, J Peters The Journal of Machine Learning Research 19 (1), 1309-1342, 2018 | 210 | 2018 |
| Learning independent causal mechanisms G Parascandolo, N Kilbertus, M Rojas-Carulla, B Schölkopf International Conference on Machine Learning, 4036-4044, 2018 | 113 | 2018 |
| Discriminative k-shot learning using probabilistic models M Bauer, M Rojas-Carulla, JB Świątkowski, B Schölkopf, RE Turner arXiv preprint arXiv:1706.00326, 2017 | 52 | 2017 |
| DeepMAsED: evaluating the quality of metagenomic assemblies O Mineeva, M Rojas-Carulla, RE Ley, B Schölkopf, ND Youngblut Bioinformatics 36 (10), 3011-3017, 2020 | 18 | 2020 |
| Genet: Deep representations for metagenomics M Rojas-Carulla, I Tolstikhin, G Luque, N Youngblut, R Ley, B Schölkopf arXiv preprint arXiv:1901.11015, 2019 | 17 | 2019 |
| Causal discovery using proxy variables M Rojas-Carulla, M Baroni, D Lopez-Paz arXiv preprint arXiv:1702.07306, 2017 | 10 | 2017 |
| Causal transfer in machine learning M Rojas-Carulla, B Schölkopf, R Turner, J Peters arXiv preprint arXiv:1507.05333, 2015 | 10 | 2015 |
| JB Swi atkowski, B. Schölkopf, and RE Turner. Discriminative k-shot learning using probabilistic models M Bauer, M Rojas-Carulla arXiv preprint arXiv:1706.00326, 2017 | 8 | 2017 |
| Recommendations on test datasets for evaluating AI solutions in pathology A Homeyer, C Geißler, LO Schwen, F Zakrzewski, T Evans, ... arXiv preprint arXiv:2204.14226, 2022 | 1 | 2022 |
| Getting Personal with Epigenetics: Towards Machine-Learning-Assisted Precision Epigenomics A Hawkins-Hooker, G Visonà, T Narendra, M Rojas-Carulla, B Schölkopf, ... bioRxiv, 2022 | | 2022 |
| Learning Transferable Representations M Rojas-Carulla University of Cambridge, 2019 | | 2019 |
