| Sparse multi-output Gaussian processes for online medical time series prediction LF Cheng, B Dumitrascu, G Darnell, C Chivers, M Draugelis, K Li, ... BMC medical informatics and decision making 20, 1-23, 2020 | 108 | 2020 |
| netNMF-sc: leveraging gene–gene interactions for imputation and dimensionality reduction in single-cell expression analysis R Elyanow, B Dumitrascu, BE Engelhardt, BJ Raphael Genome research 30 (2), 195-204, 2020 | 87 | 2020 |
| Optimal marker gene selection for cell type discrimination in single cell analyses B Dumitrascu, S Villar, DG Mixon, BE Engelhardt Nature communications 12 (1), 1186, 2021 | 85 | 2021 |
| Deep learning for bioimage analysis in developmental biology A Hallou, HG Yevick, B Dumitrascu, V Uhlmann Development 148 (18), dev199616, 2021 | 71 | 2021 |
| Pg-ts: Improved thompson sampling for logistic contextual bandits B Dumitrascu, K Feng, B Engelhardt Advances in neural information processing systems 31, 2018 | 60 | 2018 |
| Causal network inference from gene transcriptional time-series response to glucocorticoids J Lu, B Dumitrascu, IC McDowell, B Jo, A Barrera, LK Hong, SM Leichter, ... PLoS computational biology 17 (1), e1008223, 2021 | 37 | 2021 |
| Statistical tests for detecting variance effects in quantitative trait studies B Dumitrascu, G Darnell, J Ayroles, BE Engelhardt Bioinformatics 35 (2), 200-210, 2019 | 34 | 2019 |
| In silico tissue generation and power analysis for spatial omics EAG Baker, D Schapiro, B Dumitrascu, S Vickovic, A Regev Nature Methods 20 (3), 424-431, 2023 | 32 | 2023 |
| End-to-end training of deep probabilistic CCA on paired biomedical observations G Gundersen, B Dumitrascu, JT Ash, BE Engelhardt Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, 2020 | 27 | 2020 |
| Hypergraph factorization for multi-tissue gene expression imputation R Viñas, CK Joshi, D Georgiev, P Lin, B Dumitrascu, ER Gamazon, P Liò Nature machine intelligence 5 (7), 739-753, 2023 | 22 | 2023 |
| Sequential Gaussian processes for online learning of nonstationary functions MM Zhang, B Dumitrascu, SA Williamson, BE Engelhardt IEEE Transactions on Signal Processing 71, 1539-1550, 2023 | 19 | 2023 |
| Dimensionless machine learning: Imposing exact units equivariance S Villar, W Yao, DW Hogg, B Blum-Smith, B Dumitrascu Journal of Machine Learning Research 24 (109), 1-32, 2023 | 18 | 2023 |
| Nonparametric Bayesian multiarmed bandits for single-cell experiment design F Camerlenghi, B Dumitrascu, F Ferrari, BE Engelhardt, S Favaro | 14 | 2020 |
| Bayesian nonparametric discovery of isoforms and individual specific quantification D Aguiar, LF Cheng, B Dumitrascu, F Mordelet, AA Pai, BE Engelhardt Nature communications 9 (1), 1681, 2018 | 14 | 2018 |
| Dimensionless machine learning: Imposing exact units equivariance S Villar, W Yao, DW Hogg, B Blum-Smith, B Dumitrascu arXiv preprint arXiv:2204.00887, 2022 | 11 | 2022 |
| Gene-level alignment of single-cell trajectories D Sumanaweera, C Suo, AM Cujba, D Muraro, E Dann, K Polanski, ... Nature Methods 22 (1), 68-81, 2025 | 9* | 2025 |
| Patient-specific effects of medication using latent force models with Gaussian processes LF Cheng, B Dumitrascu, M Zhang, C Chivers, M Draugelis, K Li, ... International Conference on Artificial Intelligence and Statistics, 4045-4055, 2020 | 8 | 2020 |
| Approximate latent force model inference JD Moss, FL Opolka, B Dumitrascu, P Lió arXiv preprint arXiv:2109.11851, 2021 | 7 | 2021 |
| A bayesian test to identify variance effects B Dumitrascu, G Darnell, J Ayroles, BE Engelhardt arXiv preprint arXiv:1512.01616, 2015 | 7 | 2015 |
| A computational pipeline for spatial mechano-transcriptomics A Hallou, R He, BD Simons, B Dumitrascu bioRxiv, 2023.08. 03.551894, 2023 | 6 | 2023 |
