:: Library Catalog

Imagen de Portada

Guardado en:

Detalles Bibliográficos
Autores principales:	Wang, Hongjun, Yong, Jiawei, Wang, Jiawei, Fukushima, Shintaro, Jiang, Renhe
Formato:	Preprint
Publicado:	2025
Materias:	Machine Learning Artificial Intelligence
Acceso en línea:	https://arxiv.org/abs/2512.09398
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

TrajGPT-R: Generating Urban Mobility Trajectory with Reinforcement Learning-Enhanced Generative Pre-trained Transformer
por: Wang, Jiawei, et al.
Publicado: (2026)

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

STGformer: Efficient Spatiotemporal Graph Transformer for Traffic Forecasting
por: Wang, Hongjun, et al.
Publicado: (2024)

Robust Traffic Forecasting against Spatial Shift over Years
por: Wang, Hongjun, et al.
Publicado: (2024)

How Different from the Past? Spatio-Temporal Time Series Forecasting with Self-Supervised Deviation Learning
por: Gao, Haotian, et al.
Publicado: (2025)

ELLMob: Event-Driven Human Mobility Generation with Self-Aligned LLM Framework
por: Wang, Yusong, et al.
Publicado: (2026)

TrajFlow: Nation-wide Pseudo GPS Trajectory Generation with Flow Matching Models
por: Li, Peiran, et al.
Publicado: (2026)

Routing Channel-Patch Dependencies in Time Series Forecasting with Graph Spectral Decomposition
por: Li, Dongyuan, et al.
Publicado: (2026)

CausalMob: Causal Human Mobility Prediction with LLMs-derived Human Intentions toward Public Events
por: Yang, Xiaojie, et al.
Publicado: (2024)

Resilience Inference for Supply Chains with Hypergraph Neural Network
por: Shen, Zetian, et al.
Publicado: (2025)

Evaluating the Generalization Ability of Spatiotemporal Model in Urban Scenario
por: Wang, Hongjun, et al.
Publicado: (2024)

RPN 2: On Interdependence Function Learning Towards Unifying and Advancing CNN, RNN, GNN, and Transformer
por: Zhang, Jiawei
Publicado: (2024)

Uncertainty-Aware Probabilistic Graph Neural Networks for Road-Level Traffic Accident Prediction
por: Gao, Xiaowei, et al.
Publicado: (2023)

Large Language Models as Urban Residents: An LLM Agent Framework for Personal Mobility Generation
por: Wang, Jiawei, et al.
Publicado: (2024)

Free Draft-and-Verification: Toward Lossless Parallel Decoding for Diffusion Large Language Models
por: Wu, Shutong, et al.
Publicado: (2025)

SDGF: Fusing Static and Multi-Scale Dynamic Correlations for Multivariate Time Series Forecasting
por: Wang, Shaoxun, et al.
Publicado: (2025)

Hotspot Prediction of Severe Traffic Accidents in the Federal District of Brazil
por: Lima, Vinicius, et al.
Publicado: (2023)

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

UniST-Pred: A Robust Unified Framework for Spatio-Temporal Traffic Forecasting in Transportation Networks Under Disruptions
por: Wang, Yue, et al.
Publicado: (2026)

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

Graph-Conditioned Mixture of Graph Neural Network Experts for Traffic Forecasting
por: Ghaffari, Amirhossein, et al.
Publicado: (2026)

Towards Better IncomLDL: We Are Unaware of Hidden Labels in Advance
por: Jiang, Jiecheng, et al.
Publicado: (2025)

Spatio-Temporal Partial Sensing Forecast for Long-term Traffic
por: Liu, Zibo, et al.
Publicado: (2024)

CreditAudit: 2$^\text{nd}$ Dimension for LLM Evaluation and Selection
por: Song, Yiliang, et al.
Publicado: (2026)

Label Distribution Learning from Logical Label
por: Jia, Yuheng, et al.
Publicado: (2023)

Towards Neural Scaling Laws for Time Series Foundation Models
por: Yao, Qingren, et al.
Publicado: (2024)

Enhancing Spatio-temporal Quantile Forecasting with Curriculum Learning: Lessons Learned
por: Yin, Du, et al.
Publicado: (2024)

SMA-Hyper: Spatiotemporal Multi-View Fusion Hypergraph Learning for Traffic Accident Prediction
por: Gao, Xiaowei, et al.
Publicado: (2024)

CITRAS: Covariate-Informed Transformer for Time Series Forecasting
por: Yamaguchi, Yosuke, et al.
Publicado: (2025)

Generalising Traffic Forecasting to Regions without Traffic Observations
por: Su, Xinyu, et al.
Publicado: (2025)

Counterfactual Explanations for Deep Learning-Based Traffic Forecasting
por: Wang, Rushan, et al.
Publicado: (2024)

UoMo: A Universal Model of Mobile Traffic Forecasting for Wireless Network Optimization
por: Chai, Haoye, et al.
Publicado: (2024)

Skillful Kilometer-Scale Regional Weather Forecasting via Global and Regional Coupling
por: Chen, Weiqi, et al.
Publicado: (2026)

A Triple-Inertial Accelerated Alternating Optimization Method for Deep Learning Training
por: Yan, Chengcheng, et al.
Publicado: (2025)

Theoretical Foundations of Scaling Law in Familial Models
por: Song, Huan, et al.
Publicado: (2025)

RPN: Reconciled Polynomial Network Towards Unifying PGMs, Kernel SVMs, MLP and KAN
por: Zhang, Jiawei
Publicado: (2024)

Toward Unifying Group Fairness Evaluation from a Sparsity Perspective
por: Sheng, Zhecheng, et al.
Publicado: (2025)

Towards a Unified Framework of Clustering-based Anomaly Detection
por: Fang, Zeyu, et al.
Publicado: (2024)

Incident-Guided Spatiotemporal Traffic Forecasting
por: Fan, Lixiang, et al.
Publicado: (2026)

Efficient Prompt Learning for Traffic Forecasting
por: Zhang, Qianru, et al.
Publicado: (2026)