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Found 4 papers, 2 papers with code
Nonlinear model reduction for operator learning
Operator learning provides methods to approximate mappings between infinite-dimensional function spaces.
Assessment of the suitability of degradation models for the planning of CCTV inspections of sewer pipes
This work proposes a methodology to assess their suitability to plan inspections considering three dimensions: accuracy metrics, ability to produce long-term degradation curves and explainability.
Towards exploring adversarial learning for anomaly detection in complex driving scenes
So Machine learning (ML) based anomaly detection, a technique to identify data that does not belong to the training data could be used as a safety measuring indicator during the development and operational time of such AI-based components.
Autoencoder-based Semantic Novelty Detection: Towards Dependable AI-based Systems
Thus, novelty detection - identifying data that differ in some respect from the data used for training - becomes a safety measure for system development and operation.
