Unveiling Stochasticity: Universal Multi-modal Probabilistic Modeling for Traffic Forecasting
Fuente:
arXiv
Saved in:
| Main Authors: | Xiong, Weijiang, Fonod, Robert, Geroliminis, Nikolas |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data
by: Xiong, Weijiang, et al.
Published: (2025)
by: Xiong, Weijiang, et al.
Published: (2025)
Advanced computer vision for extracting georeferenced vehicle trajectories from drone imagery
by: Fonod, Robert, et al.
Published: (2024)
by: Fonod, Robert, et al.
Published: (2024)
Unveiling the Inflexibility of Adaptive Embedding in Traffic Forecasting
by: Wang, Hongjun, et al.
Published: (2024)
by: Wang, Hongjun, et al.
Published: (2024)
Stochastic Diffusion: A Diffusion Probabilistic Model for Stochastic Time Series Forecasting
by: Liu, Yuansan, et al.
Published: (2024)
by: Liu, Yuansan, et al.
Published: (2024)
Generic Multi-modal Representation Learning for Network Traffic Analysis
by: Gioacchini, Luca, et al.
Published: (2024)
by: Gioacchini, Luca, et al.
Published: (2024)
UoMo: A Universal Model of Mobile Traffic Forecasting for Wireless Network Optimization
by: Chai, Haoye, et al.
Published: (2024)
by: Chai, Haoye, et al.
Published: (2024)
Multi-scale Traffic Pattern Bank for Cross-city Few-shot Traffic Forecasting
by: Liu, Zhanyu, et al.
Published: (2024)
by: Liu, Zhanyu, et al.
Published: (2024)
Generalising Traffic Forecasting to Regions without Traffic Observations
by: Su, Xinyu, et al.
Published: (2025)
by: Su, Xinyu, et al.
Published: (2025)
Controllable Probabilistic Forecasting with Stochastic Decomposition Layers
by: Schreck, John S., et al.
Published: (2025)
by: Schreck, John S., et al.
Published: (2025)
Embracing Large Language Models in Traffic Flow Forecasting
by: Zhao, Yusheng, et al.
Published: (2024)
by: Zhao, Yusheng, et al.
Published: (2024)
STMGF: An Effective Spatial-Temporal Multi-Granularity Framework for Traffic Forecasting
by: Zhao, Zhengyang, et al.
Published: (2024)
by: Zhao, Zhengyang, et al.
Published: (2024)
Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting
by: Rasul, Kashif, et al.
Published: (2023)
by: Rasul, Kashif, et al.
Published: (2023)
Multi-Grained Temporal-Spatial Graph Learning for Stable Traffic Flow Forecasting
by: Lin, Zhenan, et al.
Published: (2025)
by: Lin, Zhenan, et al.
Published: (2025)
CycloneMAE: A Scalable Multi-Task Learning Model for Global Tropical Cyclone Probabilistic Forecasting
by: Hang, Renlong, et al.
Published: (2026)
by: Hang, Renlong, et al.
Published: (2026)
Incident-Guided Spatiotemporal Traffic Forecasting
by: Fan, Lixiang, et al.
Published: (2026)
by: Fan, Lixiang, et al.
Published: (2026)
Efficient Prompt Learning for Traffic Forecasting
by: Zhang, Qianru, et al.
Published: (2026)
by: Zhang, Qianru, et al.
Published: (2026)
A Group Symmetric Stochastic Differential Equation Model for Molecule Multi-modal Pretraining
by: Liu, Shengchao, et al.
Published: (2023)
by: Liu, Shengchao, et al.
Published: (2023)
From Specific-MLLMs to Omni-MLLMs: A Survey on MLLMs Aligned with Multi-modalities
by: Jiang, Shixin, et al.
Published: (2024)
by: Jiang, Shixin, et al.
Published: (2024)
FUSE-Traffic: Fusion of Unstructured and Structured Data for Event-aware Traffic Forecasting
by: Yu, Chenyang, et al.
Published: (2025)
by: Yu, Chenyang, et al.
Published: (2025)
Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting
by: Yao, Yueyang, et al.
Published: (2025)
by: Yao, Yueyang, et al.
Published: (2025)
Revealing the Power of Masked Autoencoders in Traffic Forecasting
by: Sun, Jiarui, et al.
Published: (2023)
by: Sun, Jiarui, et al.
Published: (2023)
Probabilistic Multi-Regional Solar Power Forecasting with Any-Quantile Recurrent Neural Networks
by: Smyl, Slawek, et al.
Published: (2026)
by: Smyl, Slawek, et al.
Published: (2026)
Irregular Traffic Time Series Forecasting Based on Asynchronous Spatio-Temporal Graph Convolutional Network
by: Zhang, Weijia, et al.
Published: (2023)
by: Zhang, Weijia, et al.
Published: (2023)
Quantifying the Influences on Probabilistic Wind Power Forecasts
by: Schreiber, Jens, et al.
Published: (2018)
by: Schreiber, Jens, et al.
Published: (2018)
Stacking for Probabilistic Short-term Load Forecasting
by: Dudek, Grzegorz
Published: (2024)
by: Dudek, Grzegorz
Published: (2024)
Unified Training of Universal Time Series Forecasting Transformers
by: Woo, Gerald, et al.
Published: (2024)
by: Woo, Gerald, et al.
Published: (2024)
RDIT: Residual-based Diffusion Implicit Models for Probabilistic Time Series Forecasting
by: Lai, Chih-Yu, et al.
Published: (2025)
by: Lai, Chih-Yu, et al.
Published: (2025)
A Pretrained Probabilistic Transformer for City-Scale Traffic Volume Prediction
by: Shen, Shiyu, et al.
Published: (2025)
by: Shen, Shiyu, et al.
Published: (2025)
Counterfactual Explanations for Deep Learning-Based Traffic Forecasting
by: Wang, Rushan, et al.
Published: (2024)
by: Wang, Rushan, et al.
Published: (2024)
Rethinking Traffic Flow Forecasting: From Transition to Generatation
by: Shijiao, Li, et al.
Published: (2025)
by: Shijiao, Li, et al.
Published: (2025)
Federated Learning with Graph-Based Aggregation for Traffic Forecasting
by: Banik, Audri, et al.
Published: (2025)
by: Banik, Audri, et al.
Published: (2025)
Sim-MSTNet: sim2real based Multi-task SpatioTemporal Network Traffic Forecasting
by: Ma, Hui, et al.
Published: (2026)
by: Ma, Hui, et al.
Published: (2026)
Multi-View Neural Differential Equations for Continuous-Time Stream Data in Long-Term Traffic Forecasting
by: Liu, Zibo, et al.
Published: (2024)
by: Liu, Zibo, et al.
Published: (2024)
DG-STMTL: A Novel Graph Convolutional Network for Multi-Task Spatio-Temporal Traffic Forecasting
by: Cui, Wanna, et al.
Published: (2025)
by: Cui, Wanna, et al.
Published: (2025)
Non-stationary Diffusion For Probabilistic Time Series Forecasting
by: Ye, Weiwei, et al.
Published: (2025)
by: Ye, Weiwei, et al.
Published: (2025)
Collaborative Deterministic-Probabilistic Forecasting for Diverse Spatiotemporal Systems
by: Sheng, Zhi, et al.
Published: (2025)
by: Sheng, Zhi, et al.
Published: (2025)
Beyond Static Uncertainty: Modeling Temporal Uncertainty Dynamics for Probabilistic Time Series Forecasting
by: Wang, Yijun, et al.
Published: (2026)
by: Wang, Yijun, et al.
Published: (2026)
Spatio-Temporal Partial Sensing Forecast for Long-term Traffic
by: Liu, Zibo, et al.
Published: (2024)
by: Liu, Zibo, et al.
Published: (2024)
Error Adjustment Based on Spatiotemporal Correlation Fusion for Traffic Forecasting
by: Liu, Fuqiang, et al.
Published: (2025)
by: Liu, Fuqiang, et al.
Published: (2025)
PIMCST: Physics-Informed Multi-Phase Consensus and Spatio-Temporal Few-Shot Learning for Traffic Flow Forecasting
by: Fofanah, Abdul Joseph, et al.
Published: (2026)
by: Fofanah, Abdul Joseph, et al.
Published: (2026)
Similar Items
-
Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data
by: Xiong, Weijiang, et al.
Published: (2025) -
Advanced computer vision for extracting georeferenced vehicle trajectories from drone imagery
by: Fonod, Robert, et al.
Published: (2024) -
Unveiling the Inflexibility of Adaptive Embedding in Traffic Forecasting
by: Wang, Hongjun, et al.
Published: (2024) -
Stochastic Diffusion: A Diffusion Probabilistic Model for Stochastic Time Series Forecasting
by: Liu, Yuansan, et al.
Published: (2024) -
Generic Multi-modal Representation Learning for Network Traffic Analysis
by: Gioacchini, Luca, et al.
Published: (2024)