SPLICE: Latent Diffusion over JEPA Embeddings for Conformal Time-Series Inpainting
Long gaps in time series are difficult to reconstruct reliably, and in power systems imputed load values inform dispatch and planning. Existing generative imputers are accurate but provide no finite-sample reliability guarantees under changing conditions. We introduce SPLICE (Self-supervised Predictive Latent Inpainting with Conformal Envelopes), which couples a JEPA encoder, a conditional latent bridge, an hourly-conditioned decoder, and Adaptive Conformal Inference (ACI). Controlled ablations indicate that long-horizon fidelity is driven more by the predictive representation than by generative complexity: under a matched bridge and decoder, JEPA outperforms reconstructive VAE and contra...
| Authors | Arnaud Zinflou |
|---|---|
| Primary category | cs.LG |
| Published | 30 April 2026 |
| Last updated at source | 3 October 2026 |
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