Variable Selection with Knockoffs

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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