arXiv:2503. 24007v4 Announce Type: replace-cross Abstract: In time series forecasting, covariates represent external factors that influence target variables.
By Yosuke Yamaguchi, Issei Suemitsu, Wenpeng Wei
SETTer is a transformer-based model designed for long‑term multivariate time‑series forecasting. It introduces decoupled self‑attention and hybrid masking to better handle high dimensionality and complex relationships, while adding explainable structures to highlight discriminative patterns. Experiments on real‑world benchmarks show that SETTer outperforms state‑of‑the‑art models in 88% of scenarios.
By Abraham Ezema, Chijioke Eze, Ferdinanda Ponci, Antonello Monti
arXiv:2607. 04117v1 Announce Type: new Abstract: ERA5 seasonal climate variables contain predictive information about future glacier retreat beyond what satellite imagery alone provides, yet existing deep learning methods focus on mapping current boundaries rather than forecasting future ones.
By Arunkumar Ramachandran
The paper presents a hybrid Convolutional‑Transformer model for forecasting Antarctic sea ice concentration (SIC) on a monthly basis. It combines convolutional encoding for spatial features with factorised self‑attention to capture spatio‑temporal dependencies, and introduces two seasonal prior mechanisms: a month‑aware positional encoding and a seasonal temporal bias. Experiments show the model outperforms convolutional and recurrent baselines, with ablation studies confirming the benefits of the seasonal priors for both short‑ and long‑horizon predictions.
By Danyang Li, John Taylor, Thang Bui, Quanling Deng
arXiv:2604. 16325v3 Announce Type: replace-cross Abstract: Multivariate time series forecasting is fundamental to numerous domains such as energy, finance, and environmental monitoring, where complex temporal dependencies and cross-variable interactions pose enduring challenges.
By Xingsheng Chen, Xianpei Mu, Deyu Yi, Yilin Yuan, Xingwei He, Bo Gao, Regina Zhang, Pietro Lio, Siu-Ming Yiu
arXiv:2607. 27418v1 Announce Type: new Abstract: Long-term ship trajectory prediction is a fundamental capability for maritime safety and autonomous navigation.
By Yuan Guan, Chandler Squires, Timothy Hu, Pradeep Ravikumar