54 citations · 100 across the 5 of their papers we have counts for
5 papers
Optimal sequencing depth for single-cell RNA-sequencing in Wasserstein space
Jakwang Kim, Sharvaj Kubal, Geoffrey Schiebinger
How many samples should one collect for an empirical distribution to be as close as possible to the true population? This question is not trivial in the context of single-cell RNA-…
Trajectory inference for a branching SDE model of cell differentiation
Elias Ventre, Aden Forrow, Nitya Gadhiwala +3
A core challenge for modern biology is how to infer the trajectories of individual cells from population-level time courses of high-dimensional gene expression data. Birth and deat…
Reconstructing probabilistic trees of cellular differentiation from single-cell RNA-seq data
Miriam Shiffman, William T. Stephenson, Geoffrey Schiebinger +4
Until recently, transcriptomics was limited to bulk RNA sequencing, obscuring the underlying expression patterns of individual cells in favor of a global average. Thanks to technol…
Statistical Optimal Transport via Factored Couplings
Aden Forrow, Jan-Christian Hütter, Mor Nitzan +3
We propose a new method to estimate Wasserstein distances and optimal transport plans between two probability distributions from samples in high dimension. Unlike plug-in rules tha…
The geometry of kernelized spectral clustering
Geoffrey Schiebinger, Martin J. Wainwright, Bin Yu
Clustering of data sets is a standard problem in many areas of science and engineering. The method of spectral clustering is based on embedding the data set using a kernel function…