2 citations · 2 across the 4 of their papers we have counts for
4 papers
Tyan-WP: A Wind Power Foundation Model for Ultra-Short-Term Probabilistic Forecasting
Jiahui Huang, Ao Luo, Lei Liu +6
Global wind power capacity, especially in China, is booming, with new farms spanning diverse terrains and climates. The industry urgently needs accurate wind power foundation model…
Phys-Diff: A Physics-Inspired Latent Diffusion Model for Tropical Cyclone Forecasting
Lei Liu, Xiaoning Yu, Kang Chen +4
Tropical cyclone (TC) forecasting is critical for disaster warning and emergency response. Deep learning methods address computational challenges but often neglect physical relatio…
TimeGMM: Single-Pass Probabilistic Forecasting via Adaptive Gaussian Mixture Models with Reversible Normalization
Lei Liu, Tengyuan Liu, Hongwei Zhao +3
Probabilistic time series forecasting is crucial for quantifying future uncertainty, with significant applications in fields such as energy and finance. However, existing methods o…
Impact of Loss Weight and Model Complexity on Physics-Informed Neural Networks for Computational Fluid Dynamics
Yi En Chou, Te Hsin Liu, Chao-An Lin
Physics Informed Neural Networks offer a mesh free framework for solving PDEs but are highly sensitive to loss weight selection. We propose two dimensional analysis based weighting…