DEM: A Distilled Explanation Model for Interpretable Anomaly Detection in Physiological Sensor Networks

DEM: A Distilled Explanation Model for Interpretable Anomaly Detection in Physiological Sensor Networks | Signal Canvas | ScienceToStartup

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Proof freshness: stale
Proof status: unverified
Display score: 7/10
Last proof check: 2026-06-01
Score updated: 2026-06-01
Score fresh until: 2026-07-01
References: 0
Source count: 4
Coverage: 67%

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Canonical ID dem-a-distilled-explanation-model-for-interpretable-anomaly-detection-in-physiological-sensor-networks | Route /signal-canvas/dem-a-distilled-explanation-model-for-interpretable-anomaly-detection-in-physiological-sensor-networks

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Evidence Receipt

Route status: building

Claims: 1

References: Pending verification

Proof: Verification pending

Freshness state: computing

Source paper: DEM: A Distilled Explanation Model for Interpretable Anomaly Detection in Physiological Sensor Networks

PDF: https://arxiv.org/pdf/2605.31007v1

Repository: https://github.com/Jyotirmoy17/dem-model

Source count: 4

Coverage: 67%

Last proof check: 2026-06-01T20:23:11.970Z

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DEM: A Distilled Explanation Model for Interpretable Anomaly Detection in Physiological Sensor Networks

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