From the 1 of 7 linked papers with an AI index.
7 papers
Earth Observation Foundation Models for Terrestrial Ecohydrology: From Representation Learning to Process Inference
Yi Yu, Jian Peng, Yucheng Lin +2
Earth observation foundation models (EOFMs) are emerging as reusable representation frameworks for data-driven retrieval, prediction and process modelling within ecohydrology, whic…
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…
PhenoYieldNet: Learning Crop-Aware Phenological Responses for Multi-Crop Yield Prediction
Yu Luo, Xiaogang Zhu, Shan Zeng +4
Accurate crop yield prediction is crucial for sustainable agriculture and global food security. While existing methods are predominantly developed for single-crop prediction, they…
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…