Követés
Romain Lopez
Romain Lopez
Incoming Assistant Professor, New York University
E-mail megerősítve itt: nyu.edu - Kezdőlap
Cím
Hivatkozott rá
Hivatkozott rá
Év
Deep generative modeling for single-cell transcriptomics
R Lopez, J Regier, MB Cole, MI Jordan, N Yosef
Nature Methods 15 (12), 1053-1058, 2018
19052018
Scrublet: computational identification of cell doublets in single-cell transcriptomic data
SL Wolock, R Lopez, AM Klein
Cell Systems, 357368, 2019
18222019
A Python library for probabilistic analysis of single-cell omics data
A Gayoso*, R Lopez*, G Xing*, P Boyeau, V Valiollah Pour Amiri, J Hong, ...
Nature Biotechnology, 1-4, 2022
478*2022
Probabilistic harmonization and annotation of single-cell transcriptomics data with deep generative models
C Xu*, R Lopez*, E Mehlman*, J Regier, MI Jordan, N Yosef
Molecular Systems Biology, 2021
4612021
Joint probabilistic modeling of single-cell multi-omic data with totalVI
A Gayoso*, Z Steier*, R Lopez, J Regier, KL Nazor, A Streets, N Yosef
Nature Methods, 2021
4102021
DestVI identifies continuums of cell types in spatial transcriptomics data
R Lopez*, B Li*, H Keren-Shaul*, P Boyeau, M Kedmi, D Pilzer, A Jelinski, ...
Nature Biotechnology, 1-10, 2022
169*2022
Information Constraints on Auto-Encoding Variational Bayes
R Lopez, J Regier, N Yosef, MI Jordan
Advances in Neural Information Processing Systems, 2018
1602018
The scverse project provides a computational ecosystem for single-cell omics data analysis
I Virshup, D Bredikhin, L Heumos, G Palla, G Sturm, A Gayoso, I Kats, ...
Nature Biotechnology, 1-3, 2023
1502023
A joint model of unpaired data from scRNA-seq and spatial transcriptomics for imputing missing gene expression measurements
R Lopez*, A Nazaret*, M Langevin*, J Samaran*, J Regier*, MI Jordan, ...
ICML workshop in Computational Biology, 2019
119*2019
Enhancing scientific discoveries in molecular biology with deep generative models
R Lopez, A Gayoso, N Yosef
Molecular systems biology 16 (9), e9198, 2020
802020
Decision-Making with Auto-Encoding Variational Bayes
R Lopez, P Boyeau, N Yosef, MI Jordan, J Regier
Advances in Neural Information Processing Systems, 2020
492020
Learning Causal Representations of Single Cells via Sparse Mechanism Shift Modeling
R Lopez, N Tagasovska, S Ra, K Cho, JK Pritchard, A Regev
Causal Learning and Reasoning, 2023
452023
Large-Scale Differentiable Causal Discovery of Factor Graphs
R Lopez, JC Hütter, JK Pritchard, A Regev
Advances in Neural Information Processing Systems, 2022
452022
An Empirical Bayes Method for Differential Expression Analysis of Single Cells with Deep Generative Models
P Boyeau, J Regier, A Gayoso, MI Jordan, R Lopez, N Yosef
Proceedings of the National Academy of Sciences, 2023
342023
Learning from eXtreme Bandit Feedback
R Lopez, I Dhillon, MI Jordan
AAAI Conference in Artificial Intelligence, 2021
272021
A deep generative model for gene expression profiles from single-cell RNA sequencing
R Lopez, J Regier, M Cole, M Jordan, N Yosef
NeurIPS workshop in Computational Biology and Bay Area Machine Learning …, 2017
24*2017
Cost-Effective Incentive Allocation via Structured Counterfactual Inference
R Lopez, C Li, X Yan, J Xiong, MI Jordan, Y Qi, L Song
AAAI Conference on Artificial Intelligence, 2020
232020
Deep Generative Models for Detecting Differential Expression in Single Cells
P Boyeau, R Lopez, J Regier, A Gayoso, MI Jordan, N Yosef
Machine Learning in Computational Biology (MLCB) meeting, 2019
21*2019
NODAGS-Flow: Nonlinear Cyclic Causal Structure Learning
MG Sethuraman, R Lopez, R Mohan, F Fekri, T Biancalani, JC Hütter
International Conference on Artificial Intelligence and Statistics, 2023
152023
Sequential Optimal Experimental Design of Perturbation Screens Guided by Multi-modal Priors
K Huang, R Lopez, JC Hutter, T Kudo, A Rios, A Regev
Research in Computational Molecular Biology Conference, 2024
142024
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Cikkek 1–20