67 citations · 157 across the 44 of their papers we have counts for
44 papers
Transportable Causal Effect Estimation across Networks under Interference
Xiaojing Du, Jiuyong Li, Lin Liu +3
Estimating causal effects under network interference typically assumes that the network used for training and the network used for deployment coincide. In practice, an intervention…
Lightweight Wrappers for Adapting Time Series Foundation Models to Regional Drought Forecasting
Wentao Gao, Jiuyong Li, Lin Liu +4
Large \emph{Time Series Foundation Models} (TSFMs) demonstrate strong zero-shot forecasting capabilities across diverse domains. However, their application to regional climate fore…
Residual-Guided Multi-Resolution Refinement of Foundation Models: A Case Study in Drought Forecasting
Wentao Gao, Jiuyong Li, Lin Liu +4
Regional climate prediction presents unique challenges for time series foundation models, which typically process temporal patterns through single-pass inference. Expert climatolog…
uLEAD-TabPFN: Uncertainty-aware Dependency-based Anomaly Detection with TabPFN
Sha Lu, Jixue Liu, Stefan Peters +4
Anomaly detection in tabular data is challenging due to high dimensionality, complex feature dependencies, and heterogeneous noise. Many existing methods rely on proximity-based cu…
Identifying the Group to Intervene on to Maximize Effect Under Cross-Group Interference
Xiaojing Du, Jiuyong Li, Lin Liu +3
In many networked systems, interventions applied to one group of units can induce substantial causal effects on another group through cross-group interference pathways. Despite its…
From Noise to Precision: A Diffusion-Driven Approach to Zero-Inflated Precipitation Prediction
Wentao Gao, Jiuyong Li, Lin Liu +6
Zero-inflated data pose significant challenges in precipitation forecasting due to the predominance of zeros with sparse non-zero events. To address this, we propose the Zero Infla…