Does Joint-Embedding Predictive Architecture Pretraining Help Time Series Forecasting?
arXiv:2609.31680v1 Announce Type: new Abstract: Joint-embedding predictive architectures (JEPA) have emerged as a promising self-supervised pretraining paradigm for time series, learning representations by predicting target embeddings in latent space rather than reconstructing raw signals. Yet evid…
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- 2026-09-30 04:00 · arXiv cs.LG
Does Joint-Embedding Predictive Architecture Pretraining Help Time Series Forecasting?