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  • 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, K. Wu, M. Jayasuriya, E. Mehlman, M. Langevin, Y. Liu, J. Samaran, G. Misrachi, A. Nazaret, O. Clivio, C. Xu, T. Ashuach, M. Lotfollahi, V. Svensson, E. Beltrame, V. Kleshchevnikov, C. Talavera-Lopez, L. Pachter, F.J. Theis, A. Streets, M.I. Jordan, J. Regier, N. Yosef. Nature Biotechnology, 2022
  • Multi-resolution deconvolution of spatial transcriptomics data reveals continuous patterns of inflammation. R. Lopez*, B. Li*, H. Keren-Shaul*, P. Boyeau, M. Kedmi, D. Pilzer, A. Jelinski, E. David, A. Wagner, Y. Addadi, M.I. Jordan, I. Amit†, N. Yosef† bioRxiv, 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
  • Probabilistic harmonization and annotation of single-cell transcriptomics data with deep generative models. C. Xu*, R. Lopez*, E. Mehlman*, J. Regier, M.I. Jordan, N. Yosef. Molecular Systems Biology, 2021
  • Decision-making with auto-encoding variational Bayes. R. Lopez, P. Boyeau, N. Yosef, M. Jordan, J. Regier. Advances in Neural Information Processing Systems, 2020
  • Interpretable factor models of single-cell RNA-seq via variational autoencoders. V. Svensson, A. Gayoso, N. Yosef, L. Pachter. Bioinformatics, 2020
  • 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*, M.I. Jordan, N. Yosef. ICML Workshop on Computational Biology, 2019
  • 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 meeting, 2019
  • Detecting zero-inflated denes in single-cell transcriptomics data. O. Clivio, R. Lopez, J. Regier, A. Gayoso, MI. Jordan, N Yosef. Machine Learning in Computational Biology meeting, 2019
  • Information constraints on auto-encoding variational Bayes. R. Lopez, J. Regier, M. Jordan, N. Yosef. Advances in Neural Information Processing Systems, 2018
  • A deep generative model for semi-supervised classification with noisy labels. M. Langevin, E. Mehlman, J. Regier, R. Lopez, M.I. Jordan, N. Yosef. Bay Area Machine Learning Symposium, 2018
  • Deep generative modeling for single-cell transcriptomics. R. Lopez, J. Regier, MB. Cole, M. Jordan, N. Yosef. Nature Methods, 2018

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