Avoiding discrimination through causal reasoning N Kilbertus, M Rojas Carulla, G Parascandolo, M Hardt, D Janzing, ... Advances in neural information processing systems 30, 2017 | 710 | 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 | 365 | 2018 |
Learning independent causal mechanisms G Parascandolo, N Kilbertus, M Rojas-Carulla, B Schölkopf International Conference on Machine Learning, 4036-4044, 2018 | 186 | 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 | 81 | 2017 |
Recommendations on compiling test datasets for evaluating artificial intelligence solutions in pathology A Homeyer, C Geißler, LO Schwen, F Zakrzewski, T Evans, ... Modern Pathology 35 (12), 1759-1769, 2022 | 47 | 2022 |
DeepMAsED: evaluating the quality of metagenomic assemblies O Mineeva, M Rojas-Carulla, RE Ley, B Schölkopf, ND Youngblut Bioinformatics 36 (10), 3011-3017, 2020 | 35 | 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 | 25 | 2019 |
Causal discovery using proxy variables M Rojas-Carulla, M Baroni, D Lopez-Paz arXiv preprint arXiv:1702.07306, 2017 | 14 | 2017 |
The ENCODE Imputation Challenge: a critical assessment of methods for cross-cell type imputation of epigenomic profiles J Schreiber, C Boix, J wook Lee, H Li, Y Guan, CC Chang, JC Chang, ... Genome biology 24 (1), 79, 2023 | 11 | 2023 |
Causal transfer in machine learning M Rojas-Carulla, B Schölkopf, R Turner, J Peters arXiv preprint arXiv:1507.05333, 2015 | 10 | 2015 |
Getting personal with epigenetics: towards individual-specific epigenomic imputation with machine learning A Hawkins-Hooker, G Visonà, T Narendra, M Rojas-Carulla, B Schölkopf, ... Nature Communications 14 (1), 4750, 2023 | 4 | 2023 |
Getting Personal with Epigenetics: Towards Machine-Learning-Assisted Precision Epigenomics A Hawkins-Hooker, G Visonà, T Narendra, M Rojas-Carulla, B Schölkopf, ... bioRxiv, 2022.02. 11.479115, 2022 | 2 | 2022 |
Publisher Correction to: Recommendations on compiling test datasets for evaluating artificial intelligence solutions in pathology (Modern Pathology,(2022), 35, 12,(1759-1769 … A Homeyer, C Geißler, LO Schwen, F Zakrzewski, T Evans, ... | | 2022 |
Learning transferable representations M Rojas-Carulla | | 2019 |