Variable Selection with Knockoffs
Model-X Knockoffs: Using Machine Learning for Controlled High-Dimensional Variable Selection - TIB AV-Portal
Deep-gKnock: Nonlinear group-feature selection with deep neural networks - ScienceDirect
The Dionne Group Stanford University
The Dionne Group Stanford University
Local false discovery rate estimation with competition‐based procedures for variable selection - Sun - 2024 - Statistics in Medicine - Wiley Online Library
The Dionne Group Stanford University
IPI PAN ZBO
Grace-AKO: a novel and stable knockoff filter for variable selection incorporating gene network structures, BMC Bioinformatics
Causal inference using deep-learning variable selection identifies and incorporates direct and indirect causalities in complex biological systems
PDF) Interpretable machine learning for genomics
Panning for Gold: Model-X Knockoffs for High-dimensional Controlled Variable Selection
GitHub - wanghaoxue0/SplitKnockoff: data adaptive variable selection framework for controlling the (directional) false discovery rate (FDR) in structural sparsity
HUB University of Washington Department of Statistics
Local false discovery rate estimation with competition‐based procedures for variable selection - Sun - 2024 - Statistics in Medicine - Wiley Online Library
Variable selection with the knockoffs: Composite null hypotheses - ScienceDirect