April 9, 2024, 4:42 a.m. | Wenxuan Zuo, Zifan Zhu, Yuxuan Du, Yi-Chun Yeh, Jed A. Fuhrman, Jinchi Lv, Yingying Fan, Fengzhu Sun

cs.LG updates on arXiv.org arxiv.org

arXiv:2404.04317v1 Announce Type: cross
Abstract: High-dimensional longitudinal time series data is prevalent across various real-world applications. Many such applications can be modeled as regression problems with high-dimensional time series covariates. Deep learning has been a popular and powerful tool for fitting these regression models. Yet, the development of interpretable and reproducible deep-learning models is challenging and remains underexplored. This study introduces a novel method, Deep Learning Inference using Knockoffs for Time series data (DeepLINK-T), focusing on the selection of significant …

abstract applications arxiv cs.lg data deep learning deep learning inference development inference knockoffs lstm popular q-bio.qm regression series stat.ml time series tool type world

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