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IMPUTATION: 作品数：95被引量：99H指数：6; 导出分析报告; 相关领域：理学更多>>; 相关作者：姜青山张学军杨森孙良丹管河山更多>>; 相关机构：华东师范大学清华大学北京市计算中心天津理工大学更多>>; 相关期刊：更多>>; 相关基金：国家自然科学基金国家教育部博士点基金广西壮族自治区自然科学基金北京市自然科学基金更多>>

High-dimensional large-scale mixed-type data imputation under missing at random: 《Science China Mathematics》2025年第4期969-1000,共32页Wei Liu Guizhen Li Ling Zhou Lan Luo; supported by National Key R&D Program of China(Grant No.2022YFA1003702);National Natural Science Foundation of China(Grant Nos.11931014 and 12271441)。; Missingness in mixed-type variables is commonly encountered in a variety of areas.The requirement of complete observations necessitates data imputation when a moderate or large proportion of data is missing.However,in...; 关键词：IMPUTATION high-dimensional mixed-type data missing at random generalized factor model

Improving Multi-task GNNs for Molecular Property Prediction via Missing Label Imputation: 《Machine Intelligence Research》2025年第1期131-144,共14页Fenyu Hu Dingshuo Chen Qiang Liu Shu Wu; supported by the National Natural Science Foundation of China(Nos.62141608 and U19B 2038),the CAAI Huawei MindSpore Open Fund.; The prediction of molecular properties is a fundamental task in the field of drug discovery.Recently,graph neural networks(GNNs)have been gaining prominence in this area.Since a molecule tends to have multiple correla...; 关键词：Graph classification imbalance learning prediction bias mixture of experts multiview representations

A Modified Deep Residual-Convolutional Neural Network for Accurate Imputation of Missing Data: 《Computers, Materials & Continua》2025年第2期3419-3441,共23页Firdaus Firdaus Siti Nurmaini Anggun Islami Annisa Darmawahyuni Ade Iriani Sapitri Muhammad Naufal Rachmatullah Bambang Tutuko Akhiar Wista Arum Muhammad Irfan Karim Yultrien Yultrien Ramadhana Noor Salassa Wandya; supported by the Intelligent System Research Group(ISysRG);supported by Universitas Sriwijaya funded by the Competitive Research 2024.; Handling missing data accurately is critical in clinical research, where data quality directly impacts decision-making and patient outcomes. While deep learning (DL) techniques for data imputation have gained attentio...; 关键词：Data imputation missing data deep learning deep residual convolutional neural network

Traffic volume imputation using the attention-based spatiotemporal generative adversarial imputation network: 《Transportation Safety and Environment》2024年第4期54-67,共14页Yixin Duan Chengcheng Wang Chao Wang Jinjun Tang Qun Chen; funded in part by Key R&D Program of Hunan Province(Grant No.2023GK2014);Key technology projects in the transportation industry(Grant No.2022-ZD6-077);Transportation Science and Technology Plan Project of Shandong Transportation Department(Grant No.2022B62);the Fundamental Research Funds for the Central Universities of Central South University(Grant No.2023ZZTS0683)。; With the increasing development of intelligent detection devices,a vast amount of traffic flow data can be collected from intelligent transportation systems.However,these data often encounter issues such as missing an...; 关键词：missing data imputation generative adversarial network spatiotemporal traffic flow data attention mechanism

An Enhanced Integrated Method for Healthcare Data Classification with Incompleteness: 《Computers, Materials & Continua》2024年第11期3125-3145,共21页Sonia Goel Meena Tushir Jyoti Arora Tripti Sharma Deepali Gupta Ali Nauman Ghulam Muhammad; supported by the Researchers Supporting Project number(RSP2024R 34),King Saud University,Riyadh,Saudi Arabia。; In numerous real-world healthcare applications,handling incomplete medical data poses significant challenges for missing value imputation and subsequent clustering or classification tasks.Traditional approaches often ...; 关键词：Incomplete data nearest neighbor linear interpolation IMPUTATION CLUSTERING CLASSIFICATION

Scalable Temporal Dimension Preserved Tensor Completion for Missing Traffic Data Imputation With Orthogonal Initialization: 《IEEE/CAA Journal of Automatica Sinica》2024年第10期2188-2190,共3页Hong Chen Mingwei Lin Jiaqi Liu Zeshui Xu; supported by the Young Top Talent of Young Eagle Program of Fujian Province,China(F21E 0011202B01).; Dear Editor,This letter puts forward a novel scalable temporal dimension preserved tensor completion model based on orthogonal initialization for missing traffic data(MTD)imputation.The MTD imputation acts directly on...; 关键词：DIMENSION management traffic

Diagnostic Measures for Functional Linear Model with Nonignorable Missing Responses: 《Communications in Mathematics and Statistics》2024年第3期543-562,共20页Yujian Zhu Puying Zhao; supported by the General Project of National Natural Science Foundation of China(Grant No.12071416).; Assessing the influence of individual observations of the functional linear models is important and challenging,especially when the observations are subject to missingness.In this paper,we introduce three case-deletio...; 关键词：Case deletion Diagnostic measure Functional linear model Nonignorable nonresponse Semiparametric imputation

Evidence of the Great Attractor and Great Repeller from Artificial Neural Network Imputation of Sloan Digital Sky Survey: 《Journal of High Energy Physics, Gravitation and Cosmology》2024年第3期1178-1194,共17页Christopher Cillian O’Neill; The Sloane Digital Sky Survey (SDSS) has been in the process of creating a 3D digital map of the Universe, since 2000AD. However, it has not been able to map that portion of the sky which is occluded by the dust gas a...; 关键词：Artificial Neural Networks Convolutional Neural Networks SDSS ANISOTROPIES Great Attractor

Missing Data Imputation: A Comprehensive Review: 《Journal of Computer and Communications》2024年第11期53-75,共23页Majed Alwateer El-Sayed Atlam Mahmoud Mohammed Abd El-Raouf Osama A. Ghoneim Ibrahim Gad; Missing data presents a significant challenge in statistical analysis and machine learning, often resulting in biased outcomes and diminished efficiency. This comprehensive review investigates various imputation techn...; 关键词：Missing Data Machine Learning PREDICTION Deep Learning IMPUTATION

A Study of EM Algorithm as an Imputation Method: A Model-Based Simulation Study with Application to a Synthetic Compositional Data: 《Open Journal of Modelling and Simulation》2024年第2期33-42,共10页Yisa Adeniyi Abolade Yichuan Zhao; Compositional data, such as relative information, is a crucial aspect of machine learning and other related fields. It is typically recorded as closed data or sums to a constant, like 100%. The statistical linear mode...; 关键词：Compositional Data Linear Regression Model Least Square Method Robust Least Square Method Synthetic Data Aitchison Distance Maximum Likelihood Estimation Expectation-Maximization Algorithm k-Nearest Neighbor and Mean imputation

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