English(EN) Instrumental Variables in Continuous-Time Stochastic Processes

新的IV框架解决了连续时间随机过程中的因果推断问题

作者 PulseAugur 编辑部 · [1 个来源] · 2026-11-05 09:03

研究人员开发了一种新颖的工具变量（IV）框架，旨在解决连续时间随机过程中的因果问题。这种新方法将传统上应用于静态或离散时间设置的IV技术扩展到处理由随机微分方程（SDEs）控制的系统中未观测到的混淆。该框架在无穷小层面上编码因果效应，并使用路径值工具变量推导出矩约束，简化了像Ornstein-Uhlenbeck这样的特定过程。该方法在恢复混淆连续时间系统中的因果效应方面取得了经验成功，而其他方法则显示出偏差。 AI

影响为复杂连续时间系统中的因果推断引入了一种新方法，可能影响依赖于动态过程建模的领域。

排序理由该集群包含一篇研究论文，详细介绍了连续时间随机过程因果推断的新方法。[lever_c_demoted from research: ic=1 ai=0.7]

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Hugging Face Daily Papers TIER_1 English(EN) · 2026-11-05 09:03

连续时间随机过程中的工具变量

Causal questions often arise in systems that evolve in continuous time. While instrumental variable (IV) methods provide a principled approach to identify causal effects in static or discrete-time settings, even in the presence of unobserved confounding, they do not yet extend to…

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连续时间随机过程中的工具变量

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