Imagen de Portada

A Time-Enhanced Data Disentanglement Network for Traffic Flow Forecasting

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Jiang, Tianfan, Wu, Mei, Weng, Wenchao, Seng, Dewen, Lin, Yiqian
Formato:	Preprint
Publicado:	2025
Materias:	Artificial Intelligence
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

MHGNet: Multi-Heterogeneous Graph Neural Network for Traffic Prediction
por: Wu, Mei, et al.
Publicado: (2025)

SFADNet: Spatio-temporal Fused Graph based on Attention Decoupling Network for Traffic Prediction
por: Wu, Mei, et al.
Publicado: (2025)

Pattern-Matching Dynamic Memory Network for Dual-Mode Traffic Prediction
por: Weng, Wenchao, et al.
Publicado: (2024)

CoMemNet: Contrastive Sampling with Memory Replay Network for Continual Traffic Prediction
por: Wu, Mei, et al.
Publicado: (2026)

Enhancing LLMs for Time Series Forecasting via Structure-Guided Cross-Modal Alignment
por: Sun, Siming, et al.
Publicado: (2025)

Spatiotemporal-aware Trend-Seasonality Decomposition Network for Traffic Flow Forecasting
por: Cao, Lingxiao, et al.
Publicado: (2025)

Liquid Neural Network Models for Natural Gas Spot Price Time-Series Forecasting
por: Liu, Yiqian, et al.
Publicado: (2026)

ST-Mamba: Spatial-Temporal Mamba for Traffic Flow Estimation Recovery using Limited Data
por: Yuan, Doncheng, et al.
Publicado: (2024)

Irregular Traffic Time Series Forecasting Based on Asynchronous Spatio-Temporal Graph Convolutional Network
por: Zhang, Weijia, et al.
Publicado: (2023)

DST-GTN: Dynamic Spatio-Temporal Graph Transformer Network for Traffic Forecasting
por: Huang, Songtao, et al.
Publicado: (2024)

Multi-View Neural Differential Equations for Continuous-Time Stream Data in Long-Term Traffic Forecasting
por: Liu, Zibo, et al.
Publicado: (2024)

STGAtt: A Spatial-Temporal Unified Graph Attention Network for Traffic Flow Forecasting
por: Liang, Zhuding, et al.
Publicado: (2025)

Online Test-Time Adaptation of Spatial-Temporal Traffic Flow Forecasting
por: Guo, Pengxin, et al.
Publicado: (2024)

Small but Mighty: Enhancing Time Series Forecasting with Lightweight LLMs
por: Fan, Haoran, et al.
Publicado: (2025)

A Multi-Channel Spatial-Temporal Transformer Model for Traffic Flow Forecasting
por: Xiao, Jianli, et al.
Publicado: (2024)

Cross Space and Time: A Spatio-Temporal Unitized Model for Traffic Flow Forecasting
por: Ruan, Weilin, et al.
Publicado: (2024)

Rethinking Traffic Flow Forecasting: From Transition to Generatation
por: Shijiao, Li, et al.
Publicado: (2025)

Embracing Large Language Models in Traffic Flow Forecasting
por: Zhao, Yusheng, et al.
Publicado: (2024)

A Global-Local Graph Attention Network for Traffic Forecasting
por: Zhang, Tianchi
Publicado: (2026)

Disentangled Parameter-Efficient Linear Model for Long-Term Time Series Forecasting
por: Zhao, Yuang, et al.
Publicado: (2024)

CESNET-TimeSeries24: Time Series Dataset for Network Traffic Anomaly Detection and Forecasting
por: Koumar, Josef, et al.
Publicado: (2024)

RIPCN: A Road Impedance Principal Component Network for Probabilistic Traffic Flow Forecasting
por: Lv, Haochen, et al.
Publicado: (2025)

Considering Nonstationary within Multivariate Time Series with Variational Hierarchical Transformer for Forecasting
por: Wang, Muyao, et al.
Publicado: (2024)

Multi-Grained Temporal-Spatial Graph Learning for Stable Traffic Flow Forecasting
por: Lin, Zhenan, et al.
Publicado: (2025)

Enhancing Spatiotemporal Networks with xLSTM: A Scalar LSTM Approach for Cellular Traffic Forecasting
por: Ali, Khalid, et al.
Publicado: (2025)

FUSE-Traffic: Fusion of Unstructured and Structured Data for Event-aware Traffic Forecasting
por: Yu, Chenyang, et al.
Publicado: (2025)

TimeEmb: A Lightweight Static-Dynamic Disentanglement Framework for Time Series Forecasting
por: Xia, Mingyuan, et al.
Publicado: (2025)

A Time Series is Worth Five Experts: Heterogeneous Mixture of Experts for Traffic Flow Prediction
por: Wang, Guangyu, et al.
Publicado: (2024)

Efficient Large-Scale Traffic Forecasting with Transformers: A Spatial Data Management Perspective
por: Fang, Yuchen, et al.
Publicado: (2024)

Multi-Modal View Enhanced Large Vision Models for Long-Term Time Series Forecasting
por: Shen, ChengAo, et al.
Publicado: (2025)

Bridging the Last Mile of Prediction: Enhancing Time Series Forecasting with Conditional Guided Flow Matching
por: Xu, Huibo, et al.
Publicado: (2025)

Prediction of Highway Traffic Flow Based on Artificial Intelligence Algorithms Using California Traffic Data
por: Lee, Junseong, et al.
Publicado: (2025)

D-PAD: Deep-Shallow Multi-Frequency Patterns Disentangling for Time Series Forecasting
por: Yuan, Xiaobing, et al.
Publicado: (2024)

Unveiling the Inflexibility of Adaptive Embedding in Traffic Forecasting
por: Wang, Hongjun, et al.
Publicado: (2024)

Disentangling Long-Short Term State Under Unknown Interventions for Online Time Series Forecasting
por: Cai, Ruichu, et al.
Publicado: (2025)

From XXLTraffic to EvoXXLTraffic: Scaling Traffic Forecasting to Sensor-Evolving Networks
por: Yin, Du, et al.
Publicado: (2026)

Efficient Traffic Forecasting on Large-Scale Road Network by Regularized Adaptive Graph Convolution
por: Wu, Kaiqi, et al.
Publicado: (2025)

ADMFormer: An Adaptive-Decomposition Transformer with Time-Varying Masked Spatial Attention for Traffic Forecasting
por: Gu, Ruiwen, et al.
Publicado: (2026)

Dynamic TMoE: A Drift-Aware Dynamic Mixture of Experts Framework for Non-Stationary Time Series Forecasting
por: Zhu, Jiawen, et al.
Publicado: (2026)

TrafficLLM: Enhancing Large Language Models for Network Traffic Analysis with Generic Traffic Representation
por: Cui, Tianyu, et al.
Publicado: (2025)