Lin Liu

Advanced prediction of cardiovascular-kidney-metabolic syndrome using eight machine learning models and 24 composite indices

Minghao Li, Junyuan Xiang, Fang Xiao, Qianxiang Wang, Lin Liu, Yujia Huo, et al.

Lightweight Wrappers for Adapting Time Series Foundation Models to Regional Drought Forecasting

Wentao Gao, Jiuyong Li, Lin Liu, Thuc Duy Le, Jixue Liu, Yanchang Zhao, et al.

Large \emph{Time Series Foundation Models} (TSFMs) demonstrate strong zero-shot forecasting capabilities across diverse domains. However, their application to regional climate forecasting faces practical challenges: model weights are often proprietary, local training records are…Read more

Residual-Guided Multi-Resolution Refinement of Foundation Models: A Case Study in Drought Forecasting

Wentao Gao, Jiuyong Li, Lin Liu, Thuc Duy Le, Jixue Liu, Yanchang Zhao, et al.

Regional climate prediction presents unique challenges for time series foundation models, which typically process temporal patterns through single-pass inference. Expert climatologists, in contrast, employ multi-scale temporal analysis and iterative refinement based on systematic…Read more

FlexRC: A Flexible Multi-Point Model Order Reduction Method for Many-Port RC Networks

Yuncheng Xu, Siyuan Yin, Lin Liu, Fan Yang, Xuan Zeng, Chengtao An, et al.

Efficient model order reduction for many-port resistor-capacitor (RC) networks is essential in post-layout circuit simulation. Existing high-accuracy elimination-based methods have certain limitations, such as fixed frequency points, large reduced-order models, or high reduction…Read more

Stabilized Higher-Order Influence Functions: Statistical Theory of a Class of Bilinear Forms

Na Liu, Chang Li, Yujia Gu, Lin Liu

Higher-order influence functions, introduced in a series of articles (Robins et al., 2008, 2009a; van der Vaart, 2014; Robins et al., 2016, 2023; Liu et al., 2017), are a unified framework for constructing rate-optimal point estimates of a class of statistical functionals under v…Read more

Evaluating the Performance of Multiple Machine Learning and Deep Learning Models on Glacier Mass Balance Estimation

Yu Liao, Lin Liu, Xueyu Zhang

Glacier mass balance estimation is important for understanding glacier responses to climate change and for assessing mountain water resources. Data-driven methods are widely used, but their cross-regional transferability remains unclear, especially in High Mountain Asia (HMA), wh…Read more