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Found 3 papers, 1 papers with code
Differential Privacy for Anomaly Detection: Analyzing the Trade-off Between Privacy and Explainability
Anomaly detection (AD), also referred to as outlier detection, is a statistical process aimed at identifying observations within a dataset that significantly deviate from the expected pattern of the majority of the data.
Climbing the Ladder of Interpretability with Counterfactual Concept Bottleneck Models
"), and imagine alternative scenarios that could result in different predictions (the "What if?").
Non-Invasive Blood Pressure Estimation from ECG Using Machine Learning Techniques
When models are calibrated, the MAE decreases to 7. 72 mmHg for SBP, 9. 45 mmHg for DBP and 8. 13 mmHg for MAP.
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