Publications
Stable Differentiable Causal Discovery
Achille Nazaret*, Justin Hong*, Elham Azizi, and David Blei.
arXiv (2023). [URL].
Achille Nazaret*, Justin Hong*, Elham Azizi, and David Blei.
arXiv (2023). [URL].
BetterBoost-Inference of Gene Regulatory Networks with Perturbation Data
Achille Nazaret and Justin Hong.
GSK.ai CausalBench Challenge, Machine Learning for Drug Discovery (MLDD) Workshop at ICLR, 1st Place Prize, Oral Presentation (2023). [URL].
Achille Nazaret and Justin Hong.
GSK.ai CausalBench Challenge, Machine Learning for Drug Discovery (MLDD) Workshop at ICLR, 1st Place Prize, Oral Presentation (2023). [URL].
Deep generative modeling of transcriptional dynamics for RNA velocity analysis in single cells
Adam Gayoso, Philipp Weiler, Mohammad Lotfollahi, Dominik Klein, Justin Hong, Aaron M. Streets, Fabian J. Theis, and Nir Yosef.
Nature Methods (2023). [URL].
Adam Gayoso, Philipp Weiler, Mohammad Lotfollahi, Dominik Klein, Justin Hong, Aaron M. Streets, Fabian J. Theis, and Nir Yosef.
Nature Methods (2023). [URL].
Deep generative modeling for quantifying sample-level heterogeneity in single-cell omics
Pierre Boyeau*, Justin Hong*, Adam Gayoso, Michael Jordan, Elham Azizi, and Nir Yosef.
Machine Learning in Computational Biology (MLCB), Oral Presentation (2022). [URL].
Pierre Boyeau*, Justin Hong*, Adam Gayoso, Michael Jordan, Elham Azizi, and Nir Yosef.
Machine Learning in Computational Biology (MLCB), Oral Presentation (2022). [URL].
A Python library for probabilistic analysis of single-cell omics
Adam Gayoso*, Romain Lopez*, Galen Xing*, Pierre Boyeau, Valeh Valiollah Pour Amiri, Justin Hong, Katherine Wu, Michael Jayasuriya, Edouard Mehlman, Maxime Langevin, Yining Liu, Jules Samaran, Gabriel Misrachi, Achille Nazaret, Oscar Clivio, Chenling Xu, Tal Ashuach, Mariano Gabitto, Mohammad Lotfollahi, Valentine Svensson, Eduardo da Veiga Beltrame, Vitalii Kleshchevnikov, Carlos Talavera-López, Lior Pachter, Fabian J. Theis, Aaron Streets, Michael I. Jordan, Jeffrey Regier, and Nir Yosef.
Nature Biotechnology (2022). [URL].
Adam Gayoso*, Romain Lopez*, Galen Xing*, Pierre Boyeau, Valeh Valiollah Pour Amiri, Justin Hong, Katherine Wu, Michael Jayasuriya, Edouard Mehlman, Maxime Langevin, Yining Liu, Jules Samaran, Gabriel Misrachi, Achille Nazaret, Oscar Clivio, Chenling Xu, Tal Ashuach, Mariano Gabitto, Mohammad Lotfollahi, Valentine Svensson, Eduardo da Veiga Beltrame, Vitalii Kleshchevnikov, Carlos Talavera-López, Lior Pachter, Fabian J. Theis, Aaron Streets, Michael I. Jordan, Jeffrey Regier, and Nir Yosef.
Nature Biotechnology (2022). [URL].
Likelihood-based deconvolution of bulk gene expression data using single-cell references
Dan D. Erdmann-Pham*, Jonathan Fischer*, Justin Hong, and Yun S. Song.
Genome Research (2021). [URL].
Dan D. Erdmann-Pham*, Jonathan Fischer*, Justin Hong, and Yun S. Song.
Genome Research (2021). [URL].
A Likelihood-based Deconvolution of Bulk Gene Expression Data Using Single-cell References
Justin Hong, Dan D. Erdmann-Pham, Jonathan Fischer, and Yun S. Song.
Master’s Thesis. University of California, Berkeley, 2021. [URL].
Justin Hong, Dan D. Erdmann-Pham, Jonathan Fischer, and Yun S. Song.
Master’s Thesis. University of California, Berkeley, 2021. [URL].
Robust Federated Learning in a Heterogeneous Environment
Avishek Ghosh*, Justin Hong*, Dong Yin, and Kannan Ramchandran.
ICML Workshop on Privacy and Security in ML (2019)[URL].
Avishek Ghosh*, Justin Hong*, Dong Yin, and Kannan Ramchandran.
ICML Workshop on Privacy and Security in ML (2019)[URL].