| Deep generative modeling for single-cell transcriptomics R Lopez, J Regier, MB Cole, MI Jordan, N Yosef Nature Methods 15 (12), 1053, 2018 | 1848 | 2018 |
| 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 40 (2), 163-166, 2022 | 431 | 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 17 (1), e9620, 2021 | 411 | 2021 |
| 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 18 (3), 272-282, 2021 | 391 | 2021 |
| Stochastic cubic regularization for fast nonconvex optimization N Tripuraneni, M Stern, C Jin, J Regier, MI Jordan Advances in Neural Information Processing Systems, 2899-2908, 2018 | 202 | 2018 |
| Information constraints on auto-encoding variational bayes R Lopez, J Regier, MI Jordan, N Yosef Advances in neural information processing systems 31, 2018 | 161 | 2018 |
| 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, ... arXiv preprint arXiv:1905.02269, 2019 | 111 | 2019 |
| A deep generative model for astronomical images of galaxies J Regier, J McAuliffe, Prabhat Neural Informational Processing Systems (NIPS) Workshop: Advances in …, 2015 | 55* | 2015 |
| Decision-making with auto-encoding variational Bayes R Lopez, P Boyeau, N Yosef, M Jordan, J Regier Advances in Neural Information Processing Systems 33, 5081-5092, 2020 | 45 | 2020 |
| Rao-blackwellized stochastic gradients for discrete distributions R Liu, J Regier, N Tripuraneni, MI Jordan, J McAuliffe Advances in Neural Information Processing Systems, 2018 | 45 | 2018 |
| Celeste: Variational Inference for a Generative Model of Astronomical Images J Regier, A Miller, J McAuliffe, R Adams, M Hoffman, D Lang, D Schlegel International Conference on Machine Learning (ICML), 2015 | 42 | 2015 |
| 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 120 (21), e2209124120, 2023 | 32 | 2023 |
| Fast black-box variational inference through stochastic trust-region optimization J Regier, MI Jordan, J McAuliffe Advances in Neural Information Processing Systems (NIPS), 2399-2408, 2017 | 30 | 2017 |
| Bayesian inference for a generative model of transcriptome profiles from single-cell RNA sequencing R Lopez, J Regier, M Cole, M Jordan, N Yosef bioRxiv, 292037, 2018 | 29 | 2018 |
| Deep generative models for detecting differential expression in single cells P Boyeau, R Lopez, J Regier, A Gayoso, MI Jordan, N Yosef bioRxiv, 794289, 2019 | 19 | 2019 |
| Harmonization and annotation of single-cell transcriptomics data with deep generative models C Xu, R Lopez, E Mehlman, J Regier, MI Jordan, N Yosef bioRxiv, 532895, 2019 | 18 | 2019 |
| Variational inference for deblending crowded starfields R Liu, JD McAuliffe, J Regier, LSST Dark Energy Science Collaboration Journal of Machine Learning Research 24 (179), 1-36, 2023 | 16 | 2023 |
| System and method for retrieving and intelligently grouping definitions found in a repository of documents J Regier, U Avissar US Patent 7,747,555, 2010 | 15 | 2010 |
| Joint probabilistic modeling of paired transcriptome and proteome measurements in single cells A Gayoso, Z Steier, R Lopez, J Regier, KL Nazor, A Streets, N Yosef Biorxiv, 2020.05. 08.083337, 2020 | 14 | 2020 |
| Mini-Minimax Uncertainty Quantification for Emulators JC Regier, PB Stark SIAM/ASA Journal on Uncertainty Quantification 3 (1), 686–708, 2015 | 14 | 2015 |
Romain LopezIncoming Assistant Professor, New York UniversityVerified email at nyu.edu
