115 citations · 317 across the 9 of their papers we have counts for
9 papers
A linear adjustment based approach to posterior drift in transfer learning
Subha Maity, Diptavo Dutta, Jonathan Terhorst +2
We present a new model and methods for the posterior drift problem where the regression function in the target domain is modeled as a linear adjustment (on an appropriate scale) of…
Exact and arbitrarily accurate non-parametric two-sample tests based on rank spacings
Dan D. Erdmann-Pham, Jonathan Terhorst, Yun S. Song
A common method for deriving non-parametric tests is to reformulate a parametric test in terms of sample ranks. Despite being distribution free (even in finite samples), the result…
Explaining Groups of Points in Low-Dimensional Representations
Gregory Plumb, Jonathan Terhorst, Sriram Sankararaman +1
A common workflow in data exploration is to learn a low-dimensional representation of the data, identify groups of points in that representation, and examine the differences betwee…
Inference of Population History using Coalescent HMMs: Review and Outlook
Jeffrey P. Spence, Matthias Steinrücken, Jonathan Terhorst +1
Studying how diverse human populations are related is of historical and anthropological interest, in addition to providing a realistic null model for testing for signatures of natu…
Fundamental limits on the accuracy of demographic inference based on the sample frequency spectrum
Jonathan Terhorst, Yun S. Song
The sample frequency spectrum (SFS) of DNA sequences from a collection of individuals is a summary statistic which is commonly used for parametric inference in population genetics.…
Efficient computation of the joint sample frequency spectra for multiple populations
John A. Kamm, Jonathan Terhorst, Yun S. Song
A wide range of studies in population genetics have employed the sample frequency spectrum (SFS), a summary statistic which describes the distribution of mutant alleles at a polymo…