Adapters that map multivariate time series into a latent space let a frozen univariate foundation model produce probabilistic multivariate forecasts, improving MSE on most tested tasks.
S tochastic G radient H amiltonian M onte C arlo
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
stat.ML 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
AdaPTS: Adapting Univariate Foundation Models to Probabilistic Multivariate Time Series Forecasting
Adapters that map multivariate time series into a latent space let a frozen univariate foundation model produce probabilistic multivariate forecasts, improving MSE on most tested tasks.