| 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), 1-23, 2020 | 79* | 2020 |
| netNMF-sc: A Network Regularization Algorithm for Dimensionality Reduction and Imputation of Single-Cell Expression Data. R Elyanow, B Dumitrascu, BE Engelhardt, BJ Raphael Genome research, 2020, 297-298, 2020 | 72* | 2020 |
| Optimal marker gene selection for cell type discrimination in single cell analyses B Dumitrascu, S Villar, D Nixon, B Engelhardt Nature Communications volume 12 (1186), 2021 | 48 | 2021 |
| PG-TS: Improved Thompson Sampling for Logistic Contextual Bandits B Dumitrascu, K Feng, BE Engelhardt NeurIPS 2018 preprint arXiv:1805.07458, 2018 | 44 | 2018 |
| Deep learning for bioimage analysis in developmental biology A Hallou, HG Yevick, B Dumitrascu, V Uhlmann Development 148 (18), dev199616, 2021 | 32* | 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 | 30* | 2019 |
| End-to-end Training of Deep Probabilistic CCA on Paired Biomedical Observations G Gundersen, B Dumitrascu, JT Ash, BE Engelhardt Uncertainty in Artificial Intelligence 2019, 2019 | 21 | 2019 |
| 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 | 17 | 2021 |
| Nonparametric Bayesian multi-armed bandits for single cell experiment design F Camerlenghi, B Dumitrascu, F Ferrari, BE Engelhardt, S Favaro The Annals of Applied Statistics, https://projecteuclid.org/euclid.aoas …, 2020 | 12 | 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 | 11 | 2018 |
| Sequential Gaussian Processes for Online Learning of Nonstationary Functions MM Zhang, B Dumitrascu, SA Williamson, BE Engelhardt IEEE Transactions on Signal Processing, 2023 | 8* | 2023 |
| 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 | 8* | 2023 |
| Patient-Specific Effects of Medication Using Latent Force Models with Gaussian Processes LF Cheng, B Dumitrascu, M Zhang, C Chivers, M Draugelis, K Li, ... AISTATS 2020, 2020 | 7 | 2020 |
| 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 | 6 | 2023 |
| GT-TS: experimental design for maximizing cell type discovery in single-cell data B Dumitrascu, K Feng, BE Engelhardt bioRxiv, 386540, 2018 | 6 | 2018 |
| Approximate Latent Force Model Inference JD Moss, FL Opolka, B Dumitrascu, P Lió arXiv preprint arXiv:2109.11851, 2021 | 2 | 2021 |
| MarkerMap: nonlinear marker selection for single-cell studies N Sarwar, W Gregory, GA Kevrekidis, S Villar, B Dumitrascu arXiv preprint arXiv:2207.14106, 2022 | 1 | 2022 |
| Supplementary material to “Nonparametric Bayesian multi-armed bandits for single cell experiment design” F Camerlenghi, B Dumitrascu, F Ferrari, BE Engelhardt, S Favaro | 1 | 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, 1-15, 2023 | | 2023 |
| Gene-level alignment of single cell trajectories informs the progression of in vitro T cell differentiation D Sumanaweera, C Suo, AM Cujba, D Muraro, E Dann, K Polanski, ... bioRxiv, 2023.03. 08.531713, 2023 | | 2023 |
Barbara EngelhardtSenior Investigator, Gladstone Institutes and Professor, Stanford UniversityVerified email at stanford.edu
