Below, an asterisk (*) by the name of the authors indicates that they were co-first (i.e., equal contributions). A caret (^) indicates that the authors were co-corresponding.
- Wu A*, Singh R*^, Walsh CA, Berger B^. An econometric lens resolves cell-state parallax. Under review, 2023 (paper, via bioRxiv. http://cb.csail.mit.edu/cb/gridnet/).
- Singh R*^, Wu A*, Mudide A*, Berger B^. Unraveling causal gene regulation from the RNA velocity graph using Velorama. Under review, 2022 (paper, via bioRxiv. http://cb.csail.mit.edu/cb/velorama/). To appear at RECOMB 2023. Invited for consideration by both Cell Systems and Genome Research.
- Wu A, Markovich T^, Berger B, Hammerla N, Singh R^. Causally-guided Regularization of Graph Attention Improves Generalizability . Under review, 2022 (paper, via arXiv). In collaboration with Twitter Research.
- Singh R*^, Li J*, Tattikota S*, Liu Y, et al. Optimal transport analysis of single-cell transcriptomics directs hypotheses prioritization and validation. Under review, 2022 (paper, via bioRxiv. http://cb.csail.mit.edu/cb/haystack/).
- Singh R^*, Wu A*, Berger B^. Granger causal inference on DAGs identifies genomic loci regulating transcription . Int'l Conf. on Learning Representations (ICLR) 2022 (scored in the top ~1% of submissions) (paper, via arXiv. https://github.com/alexw16/gridnet).
- Singh R^, Berger B^. Deciphering the species-level structure of topologically associating domains. Under review, 2021 (paper, via bioRxiv. http://cb.csail.mit.edu/cb/tadmap/).
- Singh R*^, Hie B*, Narayan A, Berger B^. Schema: metric learning enables interpretable synthesis of heterogeneous single-cell modalities. Genome Biology, 2021 (paper, via the journal. http://cb.csail.mit.edu/cb/schema/).