Interweaving Marginals into Multivariate Sample Paths: Training-Free Dependence Construction for Probabilistic Time Series Foundation Models
This work studies training-free coupling of frozen TSFM marginals into multivariate forecast sample paths, finding the same pattern persists when the fixed-marginal constraint is removed and paths are sampled directly, and remains present under native multivariate backbone inference.
Jinmyeong Choi, Jin-Kwan Jang, Seul Lee et al.
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