4 papers
REnergy: A Large-Scale Benchmark for Robust Renewable Energy Forecasting under Diverse and Extreme Conditions
Zhi Sheng, Yuan Yuan, Guozhen Zhang +1
The rapid expansion of renewable energy, particularly wind and solar power, has made reliable forecasting critical for power system operations. While recent deep learning models ha…
Collaborative Deterministic-Probabilistic Forecasting for Diverse Spatiotemporal Systems
Zhi Sheng, Yuan Yuan, Yudi Zhang +2
Probabilistic forecasting is crucial for real-world spatiotemporal systems, such as climate, energy, and urban environments, where quantifying uncertainty is essential for informed…
Unveiling the Power of Noise Priors: Enhancing Diffusion Models for Mobile Traffic Prediction
Zhi Sheng, Daisy Yuan, Jingtao Ding +1
Accurate prediction of mobile traffic, i.e., network traffic from cellular base stations, is crucial for optimizing network performance and supporting urban development. However, t…
UniFlow: A Foundation Model for Unified Urban Spatio-Temporal Flow Prediction
Yuan Yuan, Jingtao Ding, Chonghua Han +3
Urban spatio-temporal flow prediction, encompassing traffic flows and crowd flows, is crucial for optimizing city infrastructure and managing traffic and emergency responses. Tradi…