8 papers
Pushing the Limits of High-Resolution Weather Forecasting through Data Scaling
Yang Zhao, Peisong Niu, Tian Zhou +5
The development of 0.1 global weather forecasting models based on machine learning (ML) is constrained by the limited availability of high-resolution data, as decades of…
Learning Video Dynamics with Predictive Differentiable Rendering
Yujin Tang, Tian Zhou, Xin Lin +5
How to accurately predict a high-fidelity future world? While the visual world is inherently continuous, existing deterministic video prediction models operate in discrete pixel sp…
Integrating Weather Foundation Model and Satellite to Enable Fine-Grained Solar Irradiance Forecasting
Ziqing Ma, Kai Ying, Xinyue Gu +7
Accurate day-ahead solar irradiance forecasting is essential for integrating solar energy into the power grid. However, it remains challenging due to the pronounced diurnal cycle a…
Bridging Past and Future: Distribution-Aware Alignment for Time Series Forecasting
Yifan Hu, Jie Yang, Tian Zhou +4
Although contrastive and other representation-learning methods have long been explored in vision and NLP, their adoption in modern time series forecasters remains limited. We belie…
Enhancing AI-Based Tropical Cyclone Track and Intensity Forecasting via Systematic Bias Correction
Peisong Niu, Haifan Zhang, Yang Zhao +6
Tropical cyclones (TCs) pose severe threats to life, infrastructure, and economies in tropical and subtropical regions, underscoring the critical need for accurate and timely forec…
Baguan-TS: A Sequence-Native In-Context Learning Model for Time Series Forecasting with Covariates
Linxiao Yang, Xue Jiang, Gezheng Xu +9
Transformers enable in-context learning (ICL) for rapid, gradient-free adaptation in time series forecasting, yet most ICL-style approaches rely on tabularized, hand-crafted featur…