Saved in:
| Main Authors: | Ma, Minbo, Tang, Kai, Li, Huan, Teng, Fei, Zhang, Dalin, Li, Tianrui |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2502.15296 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Modeling Temporal Dependencies within the Target for Long-Term Time Series Forecasting
by: Xiong, Qi, et al.
Published: (2024)
by: Xiong, Qi, et al.
Published: (2024)
CoIFNet: A Unified Framework for Multivariate Time Series Forecasting with Missing Values
by: Tang, Kai, et al.
Published: (2025)
by: Tang, Kai, et al.
Published: (2025)
Non-collective Calibrating Strategy for Time Series Forecasting
by: Wang, Bin, et al.
Published: (2025)
by: Wang, Bin, et al.
Published: (2025)
Spatio-temporal Multivariate Time Series Forecast with Chosen Variables
by: Liu, Zibo, et al.
Published: (2025)
by: Liu, Zibo, et al.
Published: (2025)
Not All Data are Good Labels: On the Self-supervised Labeling for Time Series Forecasting
by: Yang, Yuxuan, et al.
Published: (2025)
by: Yang, Yuxuan, et al.
Published: (2025)
Spatio-temporal Causal Learning for Streamflow Forecasting
by: Wan, Shu, et al.
Published: (2024)
by: Wan, Shu, et al.
Published: (2024)
Out-of-Distribution Generalization in Time Series: A Survey
by: Wu, Xin, et al.
Published: (2025)
by: Wu, Xin, et al.
Published: (2025)
Scaling Law for Time Series Forecasting
by: Shi, Jingzhe, et al.
Published: (2024)
by: Shi, Jingzhe, et al.
Published: (2024)
Bridging Classification and Reconstruction: Cooperative Time Series Anomaly Detection
by: Tang, Qideng, et al.
Published: (2026)
by: Tang, Qideng, et al.
Published: (2026)
Causally-Aware Unsupervised Feature Selection Learning
by: Shen, Zongxin, et al.
Published: (2024)
by: Shen, Zongxin, et al.
Published: (2024)
UMOD: A Novel and Effective Urban Metro Origin-Destination Flow Prediction Method
by: Xie, Peng, et al.
Published: (2024)
by: Xie, Peng, et al.
Published: (2024)
DQE: A Semantic-Aware Evaluation Metric for Time Series Anomaly Detection
by: Li, Yuewei, et al.
Published: (2026)
by: Li, Yuewei, et al.
Published: (2026)
Multi-scale Spatio-temporal Transformer-based Imbalanced Longitudinal Learning for Glaucoma Forecasting from Irregular Time Series Images
by: Yang, Xikai, et al.
Published: (2024)
by: Yang, Xikai, et al.
Published: (2024)
Self-supervised Contrastive Learning for Implicit Collaborative Filtering
by: Song, Shipeng, et al.
Published: (2024)
by: Song, Shipeng, et al.
Published: (2024)
Crime Forecasting: A Spatio-temporal Analysis with Deep Learning Models
by: Mao, Li, et al.
Published: (2025)
by: Mao, Li, et al.
Published: (2025)
E2USD: Efficient-yet-effective Unsupervised State Detection for Multivariate Time Series
by: Lai, Zhichen, et al.
Published: (2024)
by: Lai, Zhichen, et al.
Published: (2024)
Nested Spatio-Temporal Time Series Forecasting
by: Ai, Yinghao, et al.
Published: (2026)
by: Ai, Yinghao, et al.
Published: (2026)
Fully Automated Correlated Time Series Forecasting in Minutes
by: Wu, Xinle, et al.
Published: (2024)
by: Wu, Xinle, et al.
Published: (2024)
Enhancing Spatio-temporal Quantile Forecasting with Curriculum Learning: Lessons Learned
by: Yin, Du, et al.
Published: (2024)
by: Yin, Du, et al.
Published: (2024)
DarkFarseer: Robust Spatio-temporal Kriging under Graph Sparsity and Noise
by: Liang, Zhuoxuan, et al.
Published: (2025)
by: Liang, Zhuoxuan, et al.
Published: (2025)
Continual Learning for Smart City: A Survey
by: Yang, Li, et al.
Published: (2024)
by: Yang, Li, et al.
Published: (2024)
Evolving Multi-Scale Normalization for Time Series Forecasting under Distribution Shifts
by: Qin, Dalin, et al.
Published: (2024)
by: Qin, Dalin, et al.
Published: (2024)
STRGCN: Capturing Asynchronous Spatio-Temporal Dependencies for Irregular Multivariate Time Series Forecasting
by: Wang, Yulong, et al.
Published: (2025)
by: Wang, Yulong, et al.
Published: (2025)
Selective Learning for Deep Time Series Forecasting
by: Fu, Yisong, et al.
Published: (2025)
by: Fu, Yisong, et al.
Published: (2025)
TRUST-FS: Tensorized Reliable Unsupervised Multi-View Feature Selection for Incomplete Data
by: Lu, Minghui, et al.
Published: (2025)
by: Lu, Minghui, et al.
Published: (2025)
Differential Flatness-based Fast Trajectory Planning for Fixed-wing Unmanned Aerial Vehicles
by: Li, Junzhi, et al.
Published: (2024)
by: Li, Junzhi, et al.
Published: (2024)
SAMSGL: Series-Aligned Multi-Scale Graph Learning for Spatio-Temporal Forecasting
by: Zou, Xiaobei, et al.
Published: (2023)
by: Zou, Xiaobei, et al.
Published: (2023)
Gaussian Process Latent Variable Modeling for Few-shot Time Series Forecasting
by: Cheng, Yunyao, et al.
Published: (2022)
by: Cheng, Yunyao, et al.
Published: (2022)
DRAN: A Distribution and Relation Adaptive Network for Spatio-temporal Forecasting
by: Zou, Xiaobei, et al.
Published: (2025)
by: Zou, Xiaobei, et al.
Published: (2025)
Dynamic Granularity Matters: Rethinking Vision Transformers Beyond Fixed Patch Splitting
by: Yu, Qiyang, et al.
Published: (2025)
by: Yu, Qiyang, et al.
Published: (2025)
Data Driven Decision Making with Time Series and Spatio-temporal Data
by: Yang, Bin, et al.
Published: (2025)
by: Yang, Bin, et al.
Published: (2025)
Beyond Pixels: Introducing Geometric-Semantic World Priors for Video-based Embodied Models via Spatio-temporal Alignment
by: Tang, Jinzhou, et al.
Published: (2025)
by: Tang, Jinzhou, et al.
Published: (2025)
A Survey of Route Recommendations: Methods, Applications, and Opportunities
by: Zhang, Shiming, et al.
Published: (2024)
by: Zhang, Shiming, et al.
Published: (2024)
Decorrelating the Future: Joint Frequency Domain Learning for Spatio-temporal Forecasting
by: Wang, Zepu, et al.
Published: (2026)
by: Wang, Zepu, et al.
Published: (2026)
STEMO: Early Spatio-temporal Forecasting with Multi-Objective Reinforcement Learning
by: Shao, Wei, et al.
Published: (2024)
by: Shao, Wei, et al.
Published: (2024)
Does Scaling Law Apply in Time Series Forecasting?
by: Li, Zeyan, et al.
Published: (2025)
by: Li, Zeyan, et al.
Published: (2025)
Beyond Model Ranking: Predictability-Aligned Evaluation for Time Series Forecasting
by: Feng, Wanjin, et al.
Published: (2025)
by: Feng, Wanjin, et al.
Published: (2025)
Beyond MSE: Ordinal Cross-Entropy for Probabilistic Time Series Forecasting
by: Wang, Jieting, et al.
Published: (2025)
by: Wang, Jieting, et al.
Published: (2025)
Conditional Lagrangian Wasserstein Flow for Time Series Imputation
by: Qian, Weizhu, et al.
Published: (2024)
by: Qian, Weizhu, et al.
Published: (2024)
Addressing Concept Shift in Online Time Series Forecasting: Detect-then-Adapt
by: Zhang, YiFan, et al.
Published: (2024)
by: Zhang, YiFan, et al.
Published: (2024)
Similar Items
-
Modeling Temporal Dependencies within the Target for Long-Term Time Series Forecasting
by: Xiong, Qi, et al.
Published: (2024) -
CoIFNet: A Unified Framework for Multivariate Time Series Forecasting with Missing Values
by: Tang, Kai, et al.
Published: (2025) -
Non-collective Calibrating Strategy for Time Series Forecasting
by: Wang, Bin, et al.
Published: (2025) -
Spatio-temporal Multivariate Time Series Forecast with Chosen Variables
by: Liu, Zibo, et al.
Published: (2025) -
Not All Data are Good Labels: On the Self-supervised Labeling for Time Series Forecasting
by: Yang, Yuxuan, et al.
Published: (2025)