arXiv Machine Learning July 31, 2026 By Mengfei Ran, Yifeng Shen, Ruijie Guan

Doubly Robust Functional Representation Learning for Longitudinal Causal Inference with Irregular Histories

Read the original on arXiv Machine Learning →

arXiv:2607. 28567v1 Announce Type: cross Abstract: Longitudinal causal studies often record histories as irregular functional fragments: laboratory values, physiologic signals, sensor streams, and image-derived summaries measured at unequal and informative times.

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

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llms safety

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rag

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llms rag benchmarks

arXiv Machine Learning

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efficiency

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Related stories

Causal State-Space Model for Causal Inference: Estimating Longitudinal Individual Treatment Effects

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