Image de couverture de livre

Sampling-guided Heterogeneous Graph Neural Network with Temporal Smoothing for Scalable Longitudinal Data Imputation

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Zhang, Zhaoyang, Chen, Ziqi, Liu, Qiao, Xie, Jinhan, Zhu, Hongtu
Format:	Preprint
Publié:	2024
Sujets:	Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Enhancing Missing Data Imputation through Combined Bipartite Graph and Complete Directed Graph
par: Zhang, Zhaoyang, et autres
Publié: (2024)

Temporal Gaussian Copula For Clinical Multivariate Time Series Data Imputation
par: Su, Ye, et autres
Publié: (2025)

High-Dimensional Dynamic Covariance Models with Random Forests
par: Yu, Shuguang, et autres
Publié: (2025)

MH-GIN: Multi-scale Heterogeneous Graph-based Imputation Network for AIS Data (Extended Version)
par: Liu, Hengyu, et autres
Publié: (2025)

AGS-GNN: Attribute-guided Sampling for Graph Neural Networks
par: Das, Siddhartha Shankar, et autres
Publié: (2024)

HAGNN: Hybrid Aggregation for Heterogeneous Graph Neural Networks
par: Zhu, Guanghui, et autres
Publié: (2023)

Scalable Power Control/Beamforming in Heterogeneous Wireless Networks with Graph Neural Networks
par: Zhang, Xiaochen, et autres
Publié: (2021)

GRAPES: Learning to Sample Graphs for Scalable Graph Neural Networks
par: Younesian, Taraneh, et autres
Publié: (2023)

Simple and Efficient Heterogeneous Temporal Graph Neural Network
par: Wang, Yili, et autres
Publié: (2025)

Federated Incomplete Multi-View Clustering with Heterogeneous Graph Neural Networks
par: Yan, Xueming, et autres
Publié: (2024)

Interpretable Graph Neural Networks for Heterogeneous Tabular Data
par: Alkhatib, Amr, et autres
Publié: (2024)

Missingness-aware Data Imputation via AI-powered Bayesian Generative Modeling
par: Liu, Qiao
Publié: (2026)

On the Expressive Power of Subgraph Graph Neural Networks for Graphs with Bounded Cycles
par: Chen, Ziang, et autres
Publié: (2025)

Heterogeneous Temporal Hypergraph Neural Network
par: Liu, Huan, et autres
Publié: (2025)

Graph Structure Learning for Spatial-Temporal Imputation: Adapting to Node and Feature Scales
par: Yang, Xinyu, et autres
Publié: (2024)

Incremental Label Distribution Learning with Scalable Graph Convolutional Networks
par: Jia, Ziqi, et autres
Publié: (2024)

Data Imputation with Iterative Graph Reconstruction
par: Zhong, Jiajun, et autres
Publié: (2022)

NoiseHGNN: Synthesized Similarity Graph-Based Neural Network For Noised Heterogeneous Graph Representation Learning
par: Zhang, Xiong, et autres
Publié: (2024)

Causality-Aware Spatiotemporal Graph Neural Networks for Spatiotemporal Time Series Imputation
par: Jing, Baoyu, et autres
Publié: (2024)

Pavement Missing Condition Data Imputation through Collective Learning-Based Graph Neural Networks
par: Yu, Ke, et autres
Publié: (2026)

Statistical-Neural Interaction Networks for Interpretable Mixed-Type Data Imputation
par: Deng, Ou, et autres
Publié: (2026)

Data Imputation from the Perspective of Graph Dirichlet Energy
par: Zhang, Weiqi, et autres
Publié: (2023)

Exploring Topological Bias in Heterogeneous Graph Neural Networks
par: Zhang, Yihan
Publié: (2025)

Uncertainty-Aware Deep Attention Recurrent Neural Network for Heterogeneous Time Series Imputation
par: Qian, Linglong, et autres
Publié: (2024)

GLIDE: Graph-guided Leap Inference for Diffusion Estimation of Spatio-Temporal Point Processes
par: Zhou, Guanyu, et autres
Publié: (2026)

Coden: Efficient Temporal Graph Neural Networks for Continuous Prediction
par: Zhu, Zulun, et autres
Publié: (2026)

Adaptive Heterogeneous Graph Neural Networks: Bridging Heterophily and Heterogeneity
par: Chen, Qin, et autres
Publié: (2025)

Longitudinal Missing Data Imputation for Predicting Disability Stage of Patients with Multiple Sclerosis
par: Vazifehdan, Mahin, et autres
Publié: (2025)

Enhanced Pre-training of Graph Neural Networks for Million-Scale Heterogeneous Graphs
par: Sun, Shengyin, et autres
Publié: (2025)

Self-Supervised Graph Neural Networks for Enhanced Feature Extraction in Heterogeneous Information Networks
par: Wei, Jianjun, et autres
Publié: (2024)

MagiNet: Mask-Aware Graph Imputation Network for Incomplete Traffic Data
par: Zhou, Jianping, et autres
Publié: (2024)

Imputation of Longitudinal Data Using GANs: Challenges and Implications for Classification
par: Pingi, Sharon Torao, et autres
Publié: (2025)

Generative-Contrastive Heterogeneous Graph Neural Network
par: Wang, Yu, et autres
Publié: (2024)

Heterogeneous Graph Sequence Neural Networks for Dynamic Traffic Assignment
par: Liu, Tong, et autres
Publié: (2024)

End-to-End Heterogeneous Graph Neural Networks for Traffic Assignment
par: Liu, Tong, et autres
Publié: (2023)

Ada-HGNN: Adaptive Sampling for Scalable Hypergraph Neural Networks
par: Wang, Shuai, et autres
Publié: (2024)

stMCDI: Masked Conditional Diffusion Model with Graph Neural Network for Spatial Transcriptomics Data Imputation
par: Li, Xiaoyu, et autres
Publié: (2024)

Retrofitting Temporal Graph Neural Networks with Transformer
par: Huang, Qiang, et autres
Publié: (2024)

Input Snapshots Fusion for Scalable Discrete-Time Dynamic Graph Neural Networks
par: Qi, QingGuo, et autres
Publié: (2024)

DPGAN: A Dual-Path Generative Adversarial Network for Missing Data Imputation in Graphs
par: Zheng, Xindi, et autres
Publié: (2024)