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cs.LG2026
Meta-iLaD: Identifiable Latent Dynamics via Meta-Learning of Dynamics Environments
Yubo Ye, Sweekar Piya, Xiajun Jiang +1
Learning latent dynamics is central to assessing the current states and forecasting the future trajectories of high-dimensional time series. For locally-stationary latent dynamics…
cs.LG2024
Unsupervised Learning of Hybrid Latent Dynamics: A Learn-to-Identify Framework
Yubo Ye, Sumeet Vadhavkar, Xiajun Jiang +3
Modern applications increasingly require unsupervised learning of latent dynamics from high-dimensional time-series. This presents a significant challenge of identifiability: many…