3 papers
cs.AI2026
StrideDiffusion: Accelerating Diffusion Models for Time-series Generation
Du Yin, Estrid He, Julián Jerónimo Bañuelos +6
Diffusion models have become competitive generators for time series, but their practical use is limited by the large number of sequential denoising steps required at inference time…
cs.LG2026
UPLOTS: A Unified Pretrained Language Model for Constrained Time-series Generation
Du Yin, Hao Xue, Jinliang Deng +4
In time-series generation, existing approaches typically handcraft ortrain a separate model for each dataset, which hinders their scalability and fails to leverage shared temporal…
cs.LG2026
DeepLévy: Learning Heavy-Tailed Uncertainty in Highly Volatile Time Series
Yang Yang, Du Yin, Hao Xue +1
Modeling uncertainty in heavy-tailed time series remains a critical challenge for deep probabilistic forecasting models, which often struggle to capture abrupt, extreme events. Whi…