2 papers
cs.LG2026
Koopman Invariants as Drivers of Emergent Time-Series Clustering in Joint-Embedding Predictive Architectures
Pablo Ruiz-Morales, Dries Vanoost, Davy Pissoort +1
Joint-Embedding Predictive Architectures (JEPAs), a powerful class of self-supervised models, exhibit an unexplained ability to cluster time-series data by their underlying dynamic…
eess.SY2025
Data-Driven Model Identification of Unbalanced Induction Motor Dynamics and Forces using SINDYc
Emma Vancayseele, Philip Desenfans, Zifeng Gong +3
This paper identifies the stator currents, torque and unbalanced magnetic pull (UMP) of an unbalanced induction motor by the System Identification of Nonlinear Dynamics with Contro…