arXiv Machine Learning August 14, 2026 By Haochen Zhang, Jiaheng Guo, Yu-Chao Huang, Nicholas Knoz, Tianlong Chen

Represent, Then Generate: Multimodal-Conditioned Time-Series Generation under Irregular Missingness

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arXiv:2608. 12592v1 Announce Type: new Abstract: Continuous physiological time series underpin modern clinical monitoring, yet many of the most informative signals are invasive, expensive, or simply unavailable for a given patient.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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Represent, Then Generate: Multimodal-Conditioned Time-Series Generation under Irregular Missingness

PAMF: Prior-Aware Multimodal Fusion for Incomplete Time Series Data

Autoregressive EHR Foundation Models with Multimodal Inputs

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