Self-Supervised Latent Action-Conditioned World Modeling for Time Series
Time-series data play an important role in various tasks, such as weather forecasting, web traffic analysis, and speech recognition. Recently, pioneering studies have increasingly adopted Joint-Embedding Predictive Architecture (JEPA) based encoders to learn time-series representations through latent-space prediction....
Chia-Han Kuo, Chengshuai Zhao, Huan Liu et al.
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