arXiv Machine Learning By Rebecca Potts, Aiden Durrant, Rick Hackney, Georgios Leontidis

Trust-Aware Predictive Emissions Monitoring for Gas Turbine Fleets with Limited Labelled Data

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arXiv:2606. 06156v1 Announce Type: new Abstract: Machine learning-based predictive emissions monitoring systems offer a practical alternative to direct emissions measurement, but their deployment across gas turbine fleets is challenging when emissions labels are available for only a small subset of assets.

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arXiv Machine Learning
1d ago

Reliability-aware short-term roll prediction for unmanned surface vehicles via multi-task learning and adaptive centralization

The paper introduces a reliability‑aware short‑term roll prediction framework for unmanned surface vehicles (USVs) that combines a multi‑task learning architecture with an adaptive centralization strategy. The model uses a shared backbone to feed a regression head for precise roll prediction and a quantification head for confidence scoring, enabling accurate predictions alongside reliability estimates. Experiments on a real‑sea dataset show that the approach effectively quantifies prediction reliability and generalizes well across varying operational conditions.

By Kaizhen Li, Xi Zhou, Zihao Wang, Dan Zhang, Jianjian Liu, Xiaowei Li
arXiv Machine Learning
Sep 14

PLSP (Pre-hoc Liminal Space Profiling): OOD Prediction over Detection -- An Anticipatory Approach for Machine Learning Model Reliability

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By Vipul Bansal, Himanshu Buckchash, Balasubramanian Raman, Deepak Dhungana