Researchers have developed CTRL-FM, a novel framework for virtual sensing that addresses the challenge of long-horizon node outages. Unlike existing methods that impose fixed structural biases, CTRL-FM dynamically selects and adapts structural guidance at inference time based on the specific outage conditions. This approach uses observed measurements to construct proxy outages, enabling the selection of optimal control policies (uncontrolled, graph-dominant, temporal-dominant, or balanced) and local modulation based on estimated reliability. CTRL-FM demonstrates superior performance across multiple datasets under significant sensor loss, outperforming methods with fixed structural priors. AI
IMPACT This research could improve the robustness of sensor networks in critical infrastructure by enabling more accurate data imputation during outages.
RANK_REASON The item is an academic paper detailing a new technical framework for virtual sensing. [lever_c_demoted from research: ic=1 ai=1.0]
- Air-36
- alphaXiv
- aqidah
- arXiv
- CatalyzeX
- CTRL-FM
- DagsHub
- Gotit.pub
- Hugging Face
- IArxiv
- Influence Flower
- METR-LA
- PeMS08
- ScienceCast
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