Publications

2021

Romain Lopez, Inderjit Dhillon, Michael I. Jordan. Learning from eXtreme Bandit Feedback. AAAI Conference on Artificial Intelligence, 2021.

PDF Project

2020

Adam Gayoso*, Zoë Steier*, Romain Lopez, Jeffrey Regier, Kristopher L Nazor, Aaron Streets, Nir Yosef. Joint Probabilistic Modeling of Paired Transcriptome and Proteome Measurements in Single Cells. Nature Methods (in press), 2020.

PDF Code Project

Chenling Xu*, Romain Lopez*, Edouard Mehlman*, Jeffrey Regier, Michael I. Jordan, Nir Yosef. Probabilistic Harmonization and Annotation of Single-cell Transcriptomics Data with Deep Generative Models. Molecular Systems Biology (in press), 2020.

PDF Code Project

Romain Lopez, Pierre Boyeau, Nir Yosef, Michael I. Jordan, Jeffrey Regier. Decision-Making with Auto-Encoding Variational Bayes. Advances in Neural Information Processing Systems, 2020.

PDF Code Project

Romain Lopez, Adam Gayoso, Nir Yosef. Enhancing Scientific Discoveries in Molecular Biology with Deep Generative Models. Molecular Systems Biology, 2020.

PDF Project

Romain Lopez, Chenchen Li, Xiang Yan, Junwu Xiong, Michael I. Jordan, Yuan Qi, Le Song. Cost-Effective Incentive Allocation via Structured Counterfactual Inference. AAAI Conference on Artificial Intelligence, 2020.

PDF Project

2019

Adam Gayoso, Romain Lopez, Zoë Steier, Jeffrey Regier, Aaron Streets, Nir Yosef. A Joint Model of RNA Expression and Surface Protein Abundance in Single Cells. Machine Learning in Computational Biology (MLCB), 2019.

PDF Code Project

Pierre Boyeau, Romain Lopez, Jeffrey Regier, Adam Gayoso, Michael I. Jordan, Nir Yosef. Deep Generative Models for Detecting Differential Expression in Single Cells. Machine Learning in Computational Biology (MLCB), 2019.

PDF Code Project

Oscar Clivio, Romain Lopez, Jeffrey Regier, Adam Gayoso, Michael I. Jordan, Nir Yosef. Detecting Zero-Inflated Genes in Single-Cell Transcriptomics Data. Machine Learning in Computational Biology (MLCB), Spotlight talk, 2019.

PDF Code Project

Romain Lopez*, Achille Nazaret*, Maxime Langevin*, Jules Samaran*, Jeffrey Regier*, Michael I Jordan, Nir Yosef. A Joint Model of Unpaired Data from scRNA-seq and Spatial Transcriptomics for Imputing Missing Gene Expression Measurements. ICML Workshop in Computational Biology, Spotlight talk, Best student poster award, 2019.

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Samuel L. Wolock, Romain Lopez, Allon M. Klein. Scrublet: Computational Identification of Cell Doublets in Single-cell Transcriptomic Data. Cell Systems, 2019.

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2018

Romain Lopez, Jeffrey Regier, Michael B. Cole, Michael I. Jordan, Nir Yosef. Deep Generative Modeling for Single-cell Transcriptomics. Nature Methods, 2018.

PDF Code Project

Romain Lopez, Jeffrey Regier, Michael I. Jordan, Nir Yosef. Information Constraints on Auto-Encoding Variational Bayes. Advances in Neural Information Processing Systems, 2018.

PDF Code Project

Maxime Langevin, Edouard Mehlman, Jeffrey Regier, Romain Lopez, Michael I. Jordan, Nir Yosef. A Deep Generative Model for Semi-Supervised Classification with Noisy Labels. Bay Area Machine Learning Symposium, Oral presentation, 2018.

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2017

Romain Lopez, Jeffrey Regier, Michael I. Jordan, Nir Yosef. A Deep Generative Model for Gene Expression profiles from Single-cell RNA Sequencing with Application to Differential Expression. NeurIPS Machine Learning workshop in Computational Biology, Spotlight talk and Bay Area Machine Learning Symposium, Oral presentation, 2017.

PDF Code Project