SOURCE-LINKED INTELLIGENCE

Confounding-Valid Conformal Inference for Counterfactual KPIs in Wireless Networks

arXiv · AI, language, vision and robotics · article · Sep 4, 2026 · UTC

Conformal counterfactual inference enables network operators to use logged telemetry to reliably answer 'what-if' questions about network operation. These answers typically take the form of prediction sets that contain, with a user-defined probability, the key performance indicators (KPIs) that would have been observed under alternative control actions. A key challenge is that logged telemetry may omit variables used by the controller, resulting in hidden confounding and invalidating the statistical guarantees of counterfactual analysis. In principle, this issue can be addressed using randomiz

Read original source ↗ Open in workspace

recordType

paper

region

Global