Press#

Articles#

Publications#

  • 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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