4 papers · 1 filter
Liquid Latent State Dynamics for Interpretable Turbofan Degradation Modeling
Weizhi Nie, Weijie Wang, Yuting Su
Multivariate time-series models for prognostics are often evaluated by point prediction accuracy, yet their internal states rarely expose a coherent degradation process. We study l…
Prototype Latent World Model Replay for Class-Incremental Learning
Weizhi Nie, Hui Wang, Weijie Wang +1
Class-incremental learning requires a model to learn new classes while preserving decision regions for old ones. This is difficult when raw old samples are no longer available. We…
Learning a Normal World Model for Few-Shot Boundary-Calibrated Abnormality Detection
Weizhi Nie, Weichao Liu, Weijie Wang +1
Abnormality detection in complex systems faces two practical barriers: abnormal labels are scarce, and binary labels do not quantify how far an event has departed from normal behav…
Phys-JEPA: Physics-Informed Latent World Models for Multivariate Time-Series Forecasting
Weizhi Nie, Weichao Liu, Honglin Guo +1
Multivariate forecasting in physical systems requires models that predict coupled temporal variables while preserving meaningful state evolution. Deep forecasters can fit temporal…