| A Lasso multi-marker mixed model for association mapping with population structure correction B Rakitsch, C Lippert, O Stegle, K Borgwardt Bioinformatics 29 (2), 206-214, 2013 | 133 | 2013 |
| LIMIX: genetic analysis of multiple traits C Lippert, FP Casale, B Rakitsch, O Stegle BioRxiv, 003905, 2014 | 119 | 2014 |
| Efficient set tests for the genetic analysis of correlated traits FP Casale, B Rakitsch, C Lippert, O Stegle Nature methods 12 (8), 755-758, 2015 | 114 | 2015 |
| It is all in the noise: Efficient multi-task Gaussian process inference with structured residuals B Rakitsch, C Lippert, K Borgwardt, O Stegle Advances in neural information processing systems 26, 2013 | 89 | 2013 |
| Genetic architecture of nonadditive inheritance in Arabidopsis thaliana hybrids DK Seymour, E Chae, DG Grimm, C Martin Pizarro, A Habring-Müller, ... Proceedings of the National Academy of Sciences 113 (46), E7317-E7326, 2016 | 62 | 2016 |
| ccSVM: correcting Support Vector Machines for confounding factors in biological data classification L Li, B Rakitsch, K Borgwardt Bioinformatics 27 (13), i342-i348, 2011 | 43 | 2011 |
| Translating immunopeptidomics to immunotherapy‐decision‐making for patient and personalized target selection J Fritsche, B Rakitsch, F Hoffgaard, M Römer, H Schuster, DJ Kowalewski, ... Proteomics 18 (12), 1700284, 2018 | 42 | 2018 |
| Learning Gaussian processes by minimizing PAC-Bayesian generalization bounds D Reeb, A Doerr, S Gerwinn, B Rakitsch Advances in Neural Information Processing Systems 31, 2018 | 41 | 2018 |
| Genomic profiles of diversification and genotype–phenotype association in island nematode lineages A McGaughran, C Rödelsperger, DG Grimm, JM Meyer, E Moreno, ... Molecular biology and evolution 33 (9), 2257-2272, 2016 | 32 | 2016 |
| Modelling local gene networks increases power to detect trans-acting genetic effects on gene expression B Rakitsch, O Stegle Genome biology 17, 1-13, 2016 | 29 | 2016 |
| Joint genetic analysis using variant sets reveals polygenic gene-context interactions FP Casale, D Horta, B Rakitsch, O Stegle PLoS genetics 13 (4), e1006693, 2017 | 23 | 2017 |
| Learning partially known stochastic dynamics with empirical PAC Bayes M Haußmann, S Gerwinn, A Look, B Rakitsch, M Kandemir International conference on artificial intelligence and statistics, 478-486, 2021 | 20 | 2021 |
| Learning interacting dynamical systems with latent gaussian process odes Ç Yıldız, M Kandemir, B Rakitsch Advances in Neural Information Processing Systems 35, 9188-9200, 2022 | 15 | 2022 |
| Can you text what is happening? integrating pre-trained language encoders into trajectory prediction models for autonomous driving A Keysan, A Look, E Kosman, G Gürsun, J Wagner, Y Yu, B Rakitsch arXiv preprint arXiv:2309.05282, 2023 | 12 | 2023 |
| Beyond the mean-field: Structured deep Gaussian processes improve the predictive uncertainties J Lindinger, D Reeb, C Lippert, B Rakitsch Advances in Neural Information Processing Systems 33, 8498-8509, 2020 | 10 | 2020 |
| Safe active learning for multi-output gaussian processes CY Li, B Rakitsch, C Zimmer International Conference on Artificial Intelligence and Statistics, 4512-4551, 2022 | 9 | 2022 |
| Laplace approximated Gaussian process state-space models J Lindinger, B Rakitsch, C Lippert Uncertainty in Artificial Intelligence, 1199-1209, 2022 | 8 | 2022 |
| LIMIX: genetic analysis of multiple traits. bioRxiv. 2014 C Lippert, FP Casale, B Rakitsch, O Stegle doi 10 (003905), 003905, 0 | 8 | |
| Cheap and deterministic inference for deep state-space models of interacting dynamical systems A Look, M Kandemir, B Rakitsch, J Peters arXiv preprint arXiv:2305.01773, 2023 | 7 | 2023 |
| Bootstrat: population informed bootstrapping for rare variant tests H Huang, GM Peloso, D Howrigan, B Rakitsch, CJ Simon-Gabriel, ... bioRxiv, 068999, 2016 | 5 | 2016 |
