5 citations · 8 across the 3 of their papers we have counts for
3 papers
physics.ao-ph2026★ 5 cited
Collaborative Neural Networks significantly Improve Global Aerosol Retrievals From Multi-Angle Polarimeters
Guangliang Fu, Sha Lu, Meng Gao +2
We present the RemoTAP-Hybrid algorithm for global aerosol products retrieved from Multi-Angle Polarimeters (MAP), and apply it to one-year aerosol retrievals from the SPEXone MAP…
cs.LG2026
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…
cs.LG2020★ 3 cited
Dependency-based Anomaly Detection: a General Framework and Comprehensive Evaluation
Sha Lu, Lin Liu, Kui Yu +3
Anomaly detection is crucial for understanding unusual behaviors in data, as anomalies offer valuable insights. This paper introduces Dependency-based Anomaly Detection (DepAD), a…