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Mengna Liu

2 accepted papers

2026

Beyond Missing Data Imputation: Information-Theoretic Coupling of Missingness and Class Imbalance for Optimal Irregular Time Series Classification

AAAI 2026technical

Irregular time series (IRTS) are prevalent in real-world applications, where uneven sampling and missing data pose fundamental challenges to deep learning-based feature modeling. Although existing methods attempt to retain timestamp information, they often overlook the structured patterns embedded w

Cited by 0SourcePDFScholar
2025

Multi-Scale Convolutional Networks with Class-Normalized Logit Clipping for Robust Sea State Estimation from Noisy Ship Motion Data

ICRA 2025

Autonomous ships utilize automation systems to achieve unmanned navigation, driving innovation in maritime transportation. However, sea conditions, influenced by dynamic factors such as wave height, wind speed, and ocean currents, present a challenge in accurately assessing these conditions. Traditi

Cited by 0SourceScholar