Deep neural networks with controlled variable selection for the identification of putative causal genetic variants
Adjusting the Benjamini-Hochberg method for controlling the false discovery rate in knockoff assisted variable selection
ROC performance of combined, morphological, and texturefeatures with
A Powerful and Precise Feature-level Filter using Group Knockoffs
NeurIPS 2022
Seminar University of Washington Department of Statistics
2022 – 2023 Acad. Year UCLA Statistics & Data Science
IPI PAN ZBO
Controlling the False Discovery Rate via Knockoff for High Dimensional Ising Model Variable Selection
Power and FDR in simulations involving samples with diverse ancestries.
Identification of putative causal loci in whole-genome sequencing data via knockoff statistics