New closed-form drift, diffusion, and Gaussian jump generators for bridge processes enable simulation-free generative modeling of irregularly sampled time series with discontinuities, with learned generators that recover the target marginals when the model family is well specified.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
math.NA 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Trajectory Generator Matching for Time Series
New closed-form drift, diffusion, and Gaussian jump generators for bridge processes enable simulation-free generative modeling of irregularly sampled time series with discontinuities, with learned generators that recover the target marginals when the model family is well specified.