DeepPINK: reproducible feature selection in deep neural networks

4 September 2018

Yang Young Lu

Yingying Fan

Jinchi Lv

William Stafford Noble

FAtt

ArXiv PDF HTML

Papers citing "DeepPINK: reproducible feature selection in deep neural networks"

20 / 20 papers shown

Title
Error-controlled non-additive interaction discovery in machine learning models Winston Chen Yifan Jiang William Stafford Noble Yang Young Lu 50 1 0 17 Feb 2025
Feature Selection as Deep Sequential Generative Learning Wangyang Ying Dongjie Wang Haifeng Chen Yanjie Fu 41 7 0 06 Mar 2024
$Enabling tabular deep learning when $d \gg n$ with an auxiliary knowledge graph$ Enabling tabular deep learning when $d \gg n$ with an auxiliary knowledge graph Camilo Ruiz Hongyu Ren Kexin Huang J. Leskovec 25 2 0 07 Jun 2023
Graph Convolutional Network-based Feature Selection for High-dimensional and Low-sample Size Data Can Chen Scott T. Weiss Yang-Yu Liu 29 17 0 25 Nov 2022
Model-X Sequential Testing for Conditional Independence via Testing by Betting Shalev Shaer Gal Maman Yaniv Romano 30 17 0 01 Oct 2022
Sequential Attention for Feature Selection T. Yasuda M. Bateni Lin Chen Matthew Fahrbach Gang Fu Vahab Mirrokni 39 11 0 29 Sep 2022
Deep Feature Selection Using a Novel Complementary Feature Mask Yiwen Liao J. Rivoir Raphael Latty Bin Yang 24 2 0 25 Sep 2022
Learning to Increase the Power of Conditional Randomization Tests Shalev Shaer Yaniv Romano CML 28 2 0 03 Jul 2022
Error-based Knockoffs Inference for Controlled Feature Selection Xuebin Zhao Hao Chen Yingjie Wang Weifu Li Tieliang Gong Yulong Wang Feng Zheng 36 1 0 09 Mar 2022
Variable Selection with the Knockoffs: Composite Null Hypotheses Mehrdad Pournaderi Yu Xiang 30 1 0 06 Mar 2022
High-Dimensional Knockoffs Inference for Time Series Data Chien-Ming Chi Yingying Fan C. Ing Jinchi Lv AI4TS 27 6 0 18 Dec 2021
Deep neural networks with controlled variable selection for the identification of putative causal genetic variants P. H. Kassani Fred Lu Yann Le Guen Zihuai He 18 12 0 29 Sep 2021
Differentially Private Variable Selection via the Knockoff Filter Mehrdad Pournaderi Yu Xiang 24 2 0 12 Sep 2021
Interpretability and Explainability: A Machine Learning Zoo Mini-tour Ricards Marcinkevics Julia E. Vogt XAI 28 119 0 03 Dec 2020
Quick and Robust Feature Selection: the Strength of Energy-efficient Sparse Training for Autoencoders Zahra Atashgahi Ghada Sokar T. Lee Elena Mocanu Decebal Constantin Mocanu Raymond N. J. Veldhuis Mykola Pechenizkiy 19 37 0 01 Dec 2020
FsNet: Feature Selection Network on High-dimensional Biological Data Dinesh Singh Héctor Climente-González Mathis Petrovich Eiryo Kawakami M. Yamada 21 47 0 23 Jan 2020
More Powerful Selective Kernel Tests for Feature Selection Jen Ning Lim M. Yamada Wittawat Jitkrittum Y. Terada S. Matsui Hidetoshi Shimodaira 53 9 0 14 Oct 2019
Evaluating Explanation Without Ground Truth in Interpretable Machine Learning Fan Yang Mengnan Du Xia Hu XAI ELM 27 66 0 16 Jul 2019
Simple stopping criteria for information theoretic feature selection Shujian Yu José C. Príncipe 24 12 0 29 Nov 2018
Deep Knockoffs Yaniv Romano Matteo Sesia Emmanuel J. Candès BDL 18 139 0 16 Nov 2018