Supervised learning approaches including kernel estimation, random forests, additive models, and deep learning are proposed to estimate conditional covariance matrices for removing multivariate environmental influences in SHM beyond standard response surface modeling.
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2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
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FlowGuard applies continuous normalizing flows to flag out-of-distribution synthetic queries from model stealing attacks on IDS, achieving stable detection in single-client and 100-client Sybil settings unlike identity-dependent baselines.
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Removal of Multivariate Environmental Influences in Structural Health Monitoring through Conditional Covariances and Supervised Learning
Supervised learning approaches including kernel estimation, random forests, additive models, and deep learning are proposed to estimate conditional covariance matrices for removing multivariate environmental influences in SHM beyond standard response surface modeling.
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FlowGuard: Flow Matching for Identity-Independent Detection of Data-Free Model Stealing Attacks on Energy System Intrusion Detection Systems
FlowGuard applies continuous normalizing flows to flag out-of-distribution synthetic queries from model stealing attacks on IDS, achieving stable detection in single-client and 100-client Sybil settings unlike identity-dependent baselines.