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Found 3 papers, 1 papers with code
Manifold-based Test Generation for Image Classifiers
Our approach is based on the premise that patterns in a large input data space can be effectively captured in a smaller manifold space, from which similar yet novel test cases---both the input and the label---can be sampled and generated.
Manifold for Machine Learning Assurance
The increasing use of machine-learning (ML) enabled systems in critical tasks fuels the quest for novel verification and validation techniques yet grounded in accepted system assurance principles.
Input Prioritization for Testing Neural Networks
label, for a given input---is high, which significantly impacts the amount and quality of testing that can be performed.
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