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publications

Utilizing Strategic Pre-training to Reduce Overfitting: Baguan – A Pre-trained Weather Forecasting Model

Published in KDD 2025 (31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining), 2025

This paper introduces Baguan, a novel data-driven model for medium-range weather forecasting, built on a Siamese Autoencoder pre-trained in a self-supervised manner. The model effectively mitigates overfitting through strategic pre-training and demonstrates superior performance in global forecasting and downstream tasks.

Recommended citation: Peisong Niu, Ziqing Ma, Tian Zhou, Weiqi Chen, Lefei Shen, Rong Jin, Liang Sun. (2025). "Utilizing Strategic Pre-training to Reduce Overfitting: Baguan -- A Pre-trained Weather Forecasting Model." Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2025). https://arxiv.org/abs/2505.13873

talks

teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

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Teaching experience 2

Workshop, University 1, Department, 2015

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