Dynamic adaptive generative adversarial networks with multi-view temporal factorizations for hybrid recovery of missing traffic data

[1]  Lunhui Xu,et al.  Recognizing Real-Time Transfer Patterns between Metro and Bus Systems Based on Spatial–Temporal Constraints , 2022, Journal of Transportation Engineering, Part A: Systems.

[2]  Ruonan Li,et al.  ST-CRMF: Compensated Residual Matrix Factorization with Spatial-Temporal Regularization for Graph-Based Time Series Forecasting , 2022, Italian National Conference on Sensors.

[3]  C. Babu,et al.  Spatio-Temporal Constraint-Based Low Rank Matrix Completion Approaches for Road Traffic Networks , 2022, IEEE transactions on intelligent transportation systems (Print).

[4]  Salvatore Antonio Biancardo,et al.  Missing Data Repairs for Traffic Flow With Self-Attention Generative Adversarial Imputation Net , 2022, IEEE Transactions on Intelligent Transportation Systems.

[5]  Jicong Fan.  Dynamic Nonlinear Matrix Completion for Time-Varying Data Imputation , 2022, AAAI.

[6]  Ruonan Li,et al.  Deep spatial-temporal bi-directional residual optimisation based on tensor decomposition for traffic data imputation on urban road network , 2022, Applied Intelligence.

[7]  N. Aggarwal,et al.  Missing traffic data imputation using a dual-stage error-corrected boosting regressor with uncertainty estimation , 2021, Inf. Sci..

[8]  Heng Fan,et al.  GL-GAN: Adaptive Global and Local Bilevel Optimization for Generative Adversarial Network , 2021, Pattern Recognition.

[9]  Rui Zhang,et al.  Multi-View Spatial-Temporal Model for Travel Time Estimation , 2021, SIGSPATIAL/GIS.

[10]  Xiaoyu Dong,et al.  Missing data imputation for traffic congestion data based on joint matrix factorization , 2021, Knowl. Based Syst..

[11]  Xinxin Feng,et al.  Graph Spectral Regularized Tensor Completion for Traffic Data Imputation , 2021, IEEE Transactions on Intelligent Transportation Systems.

[12]  Lei Lin,et al.  Real-time spatiotemporal prediction and imputation of traffic status based on LSTM and Graph Laplacian regularized matrix factorization , 2021 .

[13]  Xinyu Chen,et al.  Low-Rank Autoregressive Tensor Completion for Spatiotemporal Traffic Data Imputation , 2021, IEEE Transactions on Intelligent Transportation Systems.

[14]  Lihui Cen,et al.  A novel cause analysis approach of grey reasoning Petri net based on matrix operations , 2021, Appl. Intell..

[15]  Jinjun Tang,et al.  Missing traffic data imputation considering approximate intervals: A hybrid structure integrating adaptive network-based inference and fuzzy rough set , 2021, Physica A: Statistical Mechanics and its Applications.

[16]  Ting Zhang,et al.  A new method of data missing estimation with FNN-based tensor heterogeneous ensemble learning for internet of vehicle , 2021, Neurocomputing.

[17]  Pan Wu,et al.  A Combined Deep Learning Method with Attention-Based LSTM Model for Short-Term Traffic Speed Forecasting , 2020 .

[18]  Xiang Li,et al.  PC-GAIN: Pseudo-label Conditional Generative Adversarial Imputation Networks for Incomplete Data , 2020, Neural Networks.

[19]  Xinyu Chen,et al.  Scalable low-rank tensor learning for spatiotemporal traffic data imputation , 2020, Transportation Research Part C: Emerging Technologies.

[20]  Arun Mallya,et al.  Generative Adversarial Networks for Image and Video Synthesis: Algorithms and Applications , 2020, Proceedings of the IEEE.

[21]  Peng Peng,et al.  GE-GAN: A novel deep learning framework for road traffic state estimation , 2020 .

[22]  Xianbin Wang,et al.  Content-Aware Traffic Data Completion in ITS Based on Generative Adversarial Nets , 2020, IEEE Transactions on Vehicular Technology.

[23]  Liang Zhao,et al.  A generative adversarial network for travel times imputation using trajectory data , 2020, Comput. Aided Civ. Infrastructure Eng..

[24]  Zheng Zhang,et al.  Generalized Incomplete Multiview Clustering With Flexible Locality Structure Diffusion , 2020, IEEE Transactions on Cybernetics.

[25]  Yonggang Wang,et al.  Estimation of missing values in heterogeneous traffic data: Application of multimodal deep learning model , 2020, Knowl. Based Syst..

[26]  Xinyu Chen,et al.  A Nonconvex Low-Rank Tensor Completion Model for Spatiotemporal Traffic Data Imputation , 2020, Transportation Research Part C: Emerging Technologies.

[27]  Ruonan Li,et al.  Nondestructive detection of frying times for soybean oil by NIR-spectroscopy technology with Adaboost-SVM (RBF) , 2020 .

[28]  Jicong Fan,et al.  Polynomial Matrix Completion for Missing Data Imputation and Transductive Learning , 2019, AAAI.

[29]  Jicong Fan,et al.  Factor Group-Sparse Regularization for Efficient Low-Rank Matrix Recovery , 2019, NeurIPS.

[30]  Lijun Sun,et al.  Bayesian Temporal Factorization for Multidimensional Time Series Prediction , 2019, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[31]  Bin Ran,et al.  Missing Value Imputation for Traffic-Related Time Series Data Based on a Multi-View Learning Method , 2019, IEEE Transactions on Intelligent Transportation Systems.

[32]  Jicong Fan,et al.  Online High Rank Matrix Completion , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[33]  Yu Zheng,et al.  Predicting Citywide Crowd Flows in Irregular Regions Using Multi-View Graph Convolutional Networks , 2019, IEEE Transactions on Knowledge and Data Engineering.

[34]  Yingsong Li,et al.  Rapid prediction of acid detergent fiber content in corn stover based on NIR-spectroscopy technology , 2019, Optik.

[35]  Lijun Sun,et al.  A Bayesian tensor decomposition approach for spatiotemporal traffic data imputation , 2019, Transportation Research Part C: Emerging Technologies.

[36]  Mihaela van der Schaar,et al.  GAIN: Missing Data Imputation using Generative Adversarial Nets , 2018, ICML.

[37]  Jicong Fan,et al.  Matrix completion by deep matrix factorization , 2018, Neural Networks.

[38]  Yingfeng Cai,et al.  Ensemble correlation-based low-rank matrix completion with applications to traffic data imputation , 2017, Knowl. Based Syst..

[39]  Inderjit S. Dhillon,et al.  Temporal Regularized Matrix Factorization for High-dimensional Time Series Prediction , 2016, NIPS.

[40]  Aaron C. Courville,et al.  Generative Adversarial Nets , 2014, NIPS.

[41]  Tamara G. Kolda,et al.  Scalable Tensor Factorizations for Incomplete Data , 2010, ArXiv.

[42]  Jieping Ye,et al.  Tensor Completion for Estimating Missing Values in Visual Data , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[43]  Emmanuel J. Candès,et al.  Exact Matrix Completion via Convex Optimization , 2008, Found. Comput. Math..

[44]  Jicong Fan.  Multi-Mode Deep Matrix and Tensor Factorization , 2022, ICLR.

[45]  Hao Li,et al.  ST-LBAGAN: Spatio-temporal learnable bidirectional attention generative adversarial networks for missing traffic data imputation , 2021, Knowl. Based Syst..