Unicorn: Scaling High-Dimensional Time Series Forecasting via Universal Correlation Modeling

In three linesUnicorn, a multi-dataset pretraining framework, bridges the trade-off between channel-independent models (scalable but ignoring dependencies) and channel-dependent models (expressive but dimension-bounded). Using a latent prototype codebook, it projects heterogeneous channels into a shared space to learn identity-agnostic, reusable correlation patterns transferable across domains.

Summary generated by Claude — human-verified