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 | 90 | 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 | 76* | 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 | 60 | 2021 |
PG-TS: Improved Thompson Sampling for Logistic Contextual Bandits B Dumitrascu, K Feng, BE Engelhardt NeurIPS 2018 preprint arXiv:1805.07458, 2018 | 53 | 2018 |
Deep learning for bioimage analysis in developmental biology A Hallou, HG Yevick, B Dumitrascu, V Uhlmann Development 148 (18), dev199616, 2021 | 46* | 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 | 38* | 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 | 28 | 2021 |
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 | 25 | 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 | 19* | 2023 |
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 | 14 | 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 | 13 | 2023 |
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 | 12 | 2018 |
Sequential Gaussian Processes for Online Learning of Nonstationary Functions MM Zhang, B Dumitrascu, SA Williamson, BE Engelhardt IEEE Transactions on Signal Processing, 2023 | 11 | 2023 |
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 | 9 | 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 |
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 | 5 | 2021 |
A computational pipeline for spatial mechano-transcriptomics A Hallou, R He, BD Simons, B Dumitrascu bioRxiv, 2023.08. 03.551894, 2023 | 3 | 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 | 1 | 2023 |
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 |