KDD

WADEPre: A Wavelet-based Decomposition Model for Extreme Precipitation Nowcasting with Multi-Scale Learning

WADEPre: 基于小波分解的极端降水现在预测模型与多尺度学习

Baitian Liu, Haiping Zhang, Huiling Yuan, Dongjing Wang, Ying Li, Feng Chen, Hao Wu

机构 * Hangzhou Dianzi University（杭州电子科技大学） ； Nanjing University（南京大学） ； Zhejiang Institute of Meteorological Sciences（浙江省气象科学研究院） 纠错

AI总结 WADEPre通过小波分解和多尺度学习提升极端降水现在预测的精度和保真度。

Comments The paper has been submitted to KDD 2026 and is currently under review

Multi-period Learning for Financial Time Series Forecasting

多周期学习用于金融时间序列预测

Xu Zhang, Zhengang Huang, Yunzhi Wu, Xun Lu, Erpeng Qi, Yunkai Chen, Zhongya Xue, Qitong Wang, Peng Wang, Wei Wang

机构 * School of Computer Science Fudan University（复旦大学计算机学院） 纠错

AI总结 本文提出多周期学习框架MLF，通过三个新模块整合多周期输入以提升金融时间序列预测的准确性和效率。

Comments The codes are available at https://github.com/Meteor-Stars/MLF. The paper is published in the ACM SIGKDD Conference on Knowledge Discovery and Data Mining, SIGKDD 2025