Romain Lopez

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Nir YosefAssociate Professor, Department of Systems Immunology, Weizmann Institute of ScienceEmail yang diverifikasi di berkeley.edu
Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyEmail yang diverifikasi di cs.berkeley.edu
Jeffrey RegierAssistant Professor, Department of Statistics, University of MichiganEmail yang diverifikasi di umich.edu
Adam GayosoGoogle DeepMindEmail yang diverifikasi di google.com
Pierre BoyeauUniversity of California, BerkeleyEmail yang diverifikasi di berkeley.edu
Allon M KleinHarvard Medical SchoolEmail yang diverifikasi di hms.harvard.edu
Jan-Christian HütterGenentechEmail yang diverifikasi di gene.com
Samuel WolockDyno TherapeuticsEmail yang diverifikasi di g.harvard.edu
Aaron StreetsUC BerkeleyEmail yang diverifikasi di berkeley.edu
Chenling Xu AntelopeLawrence Livermore National LabEmail yang diverifikasi di llnl.gov
Ido AmitProfessor of Immunology, Weizmann Institute of ScienceEmail yang diverifikasi di weizmann.ac.il
Baoguo LiWeizmann Institute of ScienceEmail yang diverifikasi di weizmann.ac.il
Jonathan K PritchardStanford UniversityEmail yang diverifikasi di stanford.edu
Jules SamaranEcole Normale SupérieureEmail yang diverifikasi di bio.ens.psl.eu
Achille NazaretPhD student, Columbia UniversityEmail yang diverifikasi di columbia.edu
Galen XingPhD student, UC BerkeleyEmail yang diverifikasi di berkeley.edu
Tommaso BiancalaniGenentechEmail yang diverifikasi di gene.com
Fabian J TheisHelmholtz Munich, Technical University of MunichEmail yang diverifikasi di helmholtz-muenchen.de
Sarah A. TeichmannUniversity of CambridgeEmail yang diverifikasi di cam.ac.uk
Isaac VirshupSoftware Engineer, Helmholtz MunichEmail yang diverifikasi di helmholtz-munich.de

Ikuti

Romain Lopez

Incoming Assistant Professor, New York University

Email yang diverifikasi di nyu.edu - Beranda

Bayesian models Machine Learning Computational Biology


Judul Urutkan menurut kutipan Urutkan menurut tahun Urutkan menurut judul	Dikutip oleh Dikutip oleh	Tahun
Deep generative modeling for single-cell transcriptomics R Lopez, J Regier, MB Cole, MI Jordan, N Yosef Nature Methods 15 (12), 1053-1058, 2018	1922	2018
Scrublet: computational identification of cell doublets in single-cell transcriptomic data SL Wolock, R Lopez, AM Klein Cell Systems, 357368, 2019	1845	2019
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	491*	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	465	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, 2021	415	2021
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	171*	2022
Information Constraints on Auto-Encoding Variational Bayes R Lopez, J Regier, N Yosef, MI Jordan Advances in Neural Information Processing Systems, 2018	161	2018
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	154	2023
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	120*	2019
Enhancing scientific discoveries in molecular biology with deep generative models R Lopez, A Gayoso, N Yosef Molecular systems biology 16 (9), e9198, 2020	80	2020
Decision-Making with Auto-Encoding Variational Bayes R Lopez, P Boyeau, N Yosef, MI Jordan, J Regier Advances in Neural Information Processing Systems, 2020	49	2020
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	47	2023
Large-Scale Differentiable Causal Discovery of Factor Graphs R Lopez, JC Hütter, JK Pritchard, A Regev Advances in Neural Information Processing Systems, 2022	45	2022
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	34	2023
Learning from eXtreme Bandit Feedback R Lopez, I Dhillon, MI Jordan AAAI Conference in Artificial Intelligence, 2021	27	2021
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	23	2020
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	16	2023
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	15	2024

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