Publications
Jones, A., Townes, W. F., Li, D., & Engelhardt, B. E.. (2022). Contrastive latent variable modeling with application to case-control sequencing experiments. Annals of Applied Statistics (AOAS; accepted).
Martinet, G., Strzalkowski, A., & Engelhardt, B. E.. (2022). Variance minimization in the Wasserstein space for invariant causal prediction. Artificial Intelligence and Statistics (AISTATS; accepted).
Cui, S., Yoo, E. C., Li, D., Laudanski, K., & Engelhardt, B. E.. (2022). Hierarchical Gaussian processes and mixtures of experts to model Covid-19 patient trajectories. Proceedings of the Pacific Symposium on Biocomputing (PSB).
Dumitrascu, B., Villar, S., Mixon, D. G., & Engelhardt, B. E.. (2021). Optimal marker gene selection for cell type discrimination in single cell analyses. Nature Communications, 12(1186).
Ash*, J., Darnell*, G., Munro*, D., & Engelhardt, B. E.. (2021). Joint analysis of gene expression levels and histological images identifies genes associated with tissue morphology. Nature Communications, 12(1609).
Chaney, A. J. B., Verma, A., Lee, Y., & Engelhardt, B. E.. Nonparametric deconvolution models.
Dumitrascu, B., Feng, K., & Engelhardt, B. E.. GT-TS: Experimental design for maximizing cell type discovery in single-cell data.
Gewirtz, A. D., Townes, W. F., & Engelhardt, B. E.. (2021). Telescoping bimodal latent Dirichlet allocation to identify expression QTLs across tissues. Cold spring harbor laboratory.