Why Not to Use Zero Imputation? Correcting Sparsity Bias in Training Neural Networks

1 June 2019

Papers citing "Why Not to Use Zero Imputation? Correcting Sparsity Bias in Training Neural Networks"

7 / 7 papers shown

Title
MSTF: Multiscale Transformer for Incomplete Trajectory Prediction Zhanwen Liu Chao Li Nan Yang Yang Wang Jiaqi Ma Guangliang Cheng Xiangmo Zhao 46 2 0 08 Jul 2024
Don't Pay Attention to the Noise: Learning Self-supervised Representations of Light Curves with a Denoising Time Series Transformer M. Morvan N. Nikolaou K. H. Yip Ingo P. Waldmann AI4TS 107 9 0 06 Jul 2022
Survival Analysis for Idiopathic Pulmonary Fibrosis using CT Images and Incomplete Clinical Data Ahmed H. Shahin Joseph Jacob Daniel C. Alexander D. Barber 20 6 0 21 Mar 2022
FedNI: Federated Graph Learning with Network Inpainting for Population-Based Disease Prediction Liang Peng Nan Wang Nicha Dvornek Xiaofeng Zhu Xiaoxiao Li FedML AI4CE 31 70 0 19 Dec 2021
Graph Convolutional Networks for Graphs Containing Missing Features Hibiki Taguchi Xin Liu T. Murata GNN 33 85 0 09 Jul 2020
Generative Imputation and Stochastic Prediction Mohammad Kachuee Kimmo Karkkainen Orpaz Goldstein Sajad Darabi Majid Sarrafzadeh 30 23 0 22 May 2019
Recurrent Neural Networks for Multivariate Time Series with Missing Values Zhengping Che S. Purushotham Kyunghyun Cho David Sontag Yan Liu AI4TS 246 1,902 0 06 Jun 2016