Bianca Dumitrascu
Cited by
Cited by
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
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
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
PG-TS: Improved Thompson Sampling for Logistic Contextual Bandits
B Dumitrascu, K Feng, BE Engelhardt
NeurIPS 2018 preprint arXiv:1805.07458, 2018
Deep learning for bioimage analysis in developmental biology
A Hallou, HG Yevick, B Dumitrascu, V Uhlmann
Development 148 (18), dev199616, 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
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
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
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, …, 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
Sequential Gaussian Processes for Online Learning of Nonstationary Functions
MM Zhang, B Dumitrascu, SA Williamson, BE Engelhardt
IEEE Transactions on Signal Processing, 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
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
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
GT-TS: experimental design for maximizing cell type discovery in single-cell data
B Dumitrascu, K Feng, BE Engelhardt
bioRxiv, 386540, 2018
Approximate Latent Force Model Inference
JD Moss, FL Opolka, B Dumitrascu, P Lió
arXiv preprint arXiv:2109.11851, 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
Supplementary material to “Nonparametric Bayesian multi-armed bandits for single cell experiment design”
F Camerlenghi, B Dumitrascu, F Ferrari, BE Engelhardt, S Favaro
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
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
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