16 citations · 45 across the 7 of their papers we have counts for
7 papers
Thinning a Wishart Random Matrix
Ameer Dharamshi, Anna Neufeld, Lucy L. Gao +2
Recent work has explored data thinning, a generalization of sample splitting that involves decomposing a (possibly matrix-valued) random variable into independent components. In th…
Decomposing Gaussians with Unknown Covariance
Ameer Dharamshi, Anna Neufeld, Lucy L. Gao +2
Common workflows in machine learning and statistics rely on the ability to partition the information in a data set into independent portions. Recent work has shown that this may be…
Discussion of "Data fission: splitting a single data point"
Anna Neufeld, Ameer Dharamshi, Lucy L. Gao +2
Leiner et al. [2023] introduce an important generalization of sample splitting, which they call data fission. They consider two cases of data fission: P1 fission and P2 fission. Wh…
Generalized Data Thinning Using Sufficient Statistics
Ameer Dharamshi, Anna Neufeld, Keshav Motwani +3
Our goal is to develop a general strategy to decompose a random variable into multiple independent random variables, without sacrificing any information about unknown parameter…
Data thinning for convolution-closed distributions
Anna Neufeld, Ameer Dharamshi, Lucy L. Gao +1
We propose data thinning, an approach for splitting an observation into two or more independent parts that sum to the original observation, and that follow the same distribution as…
Inference after latent variable estimation for single-cell RNA sequencing data
Anna Neufeld, Lucy L. Gao, Joshua Popp +2
In the analysis of single-cell RNA sequencing data, researchers often characterize the variation between cells by estimating a latent variable, such as cell type or pseudotime, rep…
Tree-Values: selective inference for regression trees
Anna C. Neufeld, Lucy L. Gao, Daniela M. Witten
We consider conducting inference on the output of the Classification and Regression Tree (CART) [Breiman et al., 1984] algorithm. A naive approach to inference that does not accoun…