6 papers
Stable Attention Response for Reliable Precipitation Nowcasting
Penghui Wen, Zexin Hu, Sen Zhang +6
The paper introduces HARECast, a framework that stabilizes attention-response energy across heads and layers to improve the reliability of precipitation nowcasting models.
GeoRoPE: Ground-Aware Rotary Adaptation for Remote Sensing Foundation Models
Yu Luo, Kun Hu, Mengwei He +7
Remote-sensing foundation models (RSFMs) benefit from pretraining on imagery from multiple sensors and ground sampling distances (GSDs), but such exposure alone does not resolve sc…
McCast: Memory-Guided Latent Drift Correction for Long-Horizon Precipitation Nowcasting
Penghui Wen, Yu Luo, Lintao Wang +4
Existing precipitation nowcasting methods typically adopt an autoregressive formulation, where future states are predicted from previous outputs. However, such an approach accumula…
DuoCast: Duo-Probabilistic Diffusion for Precipitation Nowcasting
Penghui Wen, Mengwei He, Patrick Filippi +5
Accurate short-term precipitation forecasting is critical for weather-sensitive decision-making in agriculture, transportation, and disaster response. Existing deep learning approa…
LimeSoDa: A Dataset Collection for Benchmarking of Machine Learning Regressors in Digital Soil Mapping
J. Schmidinger, S. Vogel, V. Barkov +33
Digital soil mapping (DSM) relies on a broad pool of statistical methods, yet determining the optimal method for a given context remains challenging and contentious. Benchmarking s…
Field-scale soil moisture estimated from Sentinel-1 SAR data using a knowledge-guided deep learning approach
Yi Yu, Patrick Filippi, Thomas F. A. Bishop
Soil moisture (SM) estimation from active microwave data remains challenging due to the complex interactions between radar backscatter and surface characteristics. While the water…