23 citations · 32 across the 12 of their papers we have counts for
6 papers · 1 filter
Selective Inference for Clustering Under Unknown Covariance
Yiqun T. Chen, Lucy L. Gao
Unsupervised clustering is widely used to discover underlying group structure, after which researchers often seek to validate these groups via post-hoc hypothesis testing on the po…
Power Analysis for Prediction-Powered Inference
Yiqun T. Chen, Moran Guo, Shengy Li
Modern studies increasingly leverage outcomes predicted by machine learning and artificial intelligence (AI/ML) models, and recent work, such as prediction-powered inference (PPI),…
Testing for a difference in means of a single feature after clustering
Yiqun T. Chen, Lucy L. Gao
For many applications, it is critical to interpret and validate groups of observations obtained via clustering. A common validation approach involves testing differences in feature…
Selective inference for k-means clustering
Yiqun T. Chen, Daniela M. Witten
We consider the problem of testing for a difference in means between clusters of observations identified via k-means clustering. In this setting, classical hypothesis tests lead to…
More powerful selective inference for the graph fused lasso
Yiqun T. Chen, Sean W. Jewell, Daniela M. Witten
The graph fused lasso -- which includes as a special case the one-dimensional fused lasso -- is widely used to reconstruct signals that are piecewise constant on a graph, meaning t…
Quantifying uncertainty in spikes estimated from calcium imaging data
Yiqun T. Chen, Sean W. Jewell, Daniela M. Witten
In recent years, a number of methods have been proposed to estimate the times at which a neuron spikes on the basis of calcium imaging data. However, quantifying the uncertainty as…